ijltnc v1(1)

Volume 1 No.1 June, 2011

Copyright © ExcelingTech Publisher, United Kingdom

Web: excelingtech.co.uk ojs.excelingtech.co.uk/index.php/IJLTNC

Editorial Board Editor in Chief

Dr. Irfan Ullah, Middlesex University, London, UK

Managing Editor

Dr. Nida Aslam, Middlesex University, London, UK

Editorial Board Members

Dr. Imad Jawhar, Faculty of Information Technology, United Arab Emirates

University, UAE.

Dr. Natarajan Meghanathan, Department of Computer Science, Jackson State

University, Jackson

Table of Contents

1. Balanced Multiwavelet Based Mammogram Image Processing .............................................. 1

D.M.Garge, Dr.V.N.Bapat

2. Origin Authentication of Digitally Signed Message Using Joint Signature Scheme in

Mobile Commerce ................................................................................................................................ 6

Aihab Khan, Malik.Sikandar Hayat Khiyal, Sara Ayub

3. Non Repudiation in M- Commerce Using Joint Signature Scheme ............................... 13

Aihab Khan, Malik Sikandar Hayat Khiyal, Madiha Tariq

4. Design Issues and Applications of Wireless Body Area Sensor Networks.................... 19

Rakhshanda Yousaf, Sajjad A Madini, Aihab Khan

Int. Jour. of Latest Trends in Netw. & Comm Vol-1 No. 1 June 2011

1

Balanced Multiwavelet Based Mammogram

Image Processing

D.M.Garge#1

, Dr.V.N.Bapat#2

#1 Lecturer in Electronics, Government Polytechnic, Kolhapur, India,

#2Principal, A.D. College of Engineering, Ashta, India,

[email protected]

[email protected]

Abstract- This paper deals with the mammogram

image processing using balanced multiwavelets. The

property of balancing proves to be central to the

different issues ,like the preservation of smoothness in

images, improving the enrgy compaction ratio

etc.Using balanced multiwavelets, one can avoid the

steps of pre and post filtering, that is required with

systems based on unbalanced multiwavelets. Medical

researchers along with mathematicians and

technologists are working with mammogram images to

detect breast cancer at an early stage. Until recently,

the wavelet and multiwavelet theory has been applied

successfully in the domain of computer aided

diagnostics of cancer. However, the analytical

speculations indicate that the balanced multiwavelets

have great potential in mammogram image processing.

The present communication reports mammogram

image processing using balanced multiwavelets

implemented using MATLAB.

Keywords- Mammograms, Image Processing, Balanced

Multiwavelet, MATLAB

1. Introduction

Wavelet and multiwavelet transform is a useful tool

for signal processing applications such as image

compression and de-noising. Literature survey

reveals extensive work in the field of scalar wavelets

and multiwavelets. The latest entrant in the wavelet

paradigm are the „Balanced Multiwavelets‟. They

have several advantages such as smotthness in

scaling and wavelet functions, regularity of

multiwavelets, particularly significant in signal

processing applications; to name a few.[9] The

present paper describes implementation and

application of balanced multiwavelets for

mammogram image processing, which would play a

vital role in an early detection of the breast cancer.

We report here a simple method to generate

balanced multiwavelet of order one and two and its

application in image denoising. Experimental results

of application of balanced multiwavelets to

mammogram images have also been presented in

this paper.

While the authors have extensively dealt with the

mammogram image processing with multiwavelets

elsewhere [13], it is intended to present

experimental results regarding processing of

mammogram images using balanced multiwavelets

in the present communication.

The paper is organized as follows. At the outset, the

background information related to the breast cancer

is presented along with the literature review of

mammogram image processing techniques in

Section II. Section III describes the focus of present

work and section IV covers methodology adopted.

Section V summarizes theory of balanced

multiwavelets. At the end experimental results are

presented.

2. Literature Survey and Prior Art

Literature survey reveals that the mammograms and

their analysis by the way of image processing has

found to be on up-surge the interest of good number

of researchers. Being an interdisciplinary area of

research, there are contributions from many

disciplines such as statistics, mathematics, computer

and medical professionals and social scientists. The

role of application of statistical algorithm seems to

be dominating in this area.

The pioneering work in this area is done by Woods

K. S. et.al. [2] and Solka J. L. et. al. [3] in applying

the computer aided detection (CAD) of the Brest

cancer. Later, the techniques are refined by using

various methods such a heuristics, fuzzy reasoning,

Vector Space Machines, morphological approach

and use of adaptive wavelet transform, CAD

systems using filter banks etc. [4], [5], [6] The

research work seems to be forging on several

directions such as conceiving improved algorithms,

development of novel analytical framework,

development of custom hardware based on

programmable logic design etc.

mailto:[email protected]


mailto:%[email protected]


2

3. Focus of the Present Work

In spite of great deal of research work in this area

briefly reviewed in section II, there are still

challenges lying ahead due to inherent limitations of

the scalar wavelets and multiwavelets. Some of the

limitations are difficulty in combining the

symmetry, orthogonality and second order

approximation. Multiwavelet processing requires pre

and post filtering of signal to be processed. Balanced

Muliwavelets offer possibility of superior

performance for mammogram image processing

applications as compared with scalar wavelets and

multiwavelets. Foundational work in

conceptualizing the Multiwavelet system is reported

by Geronimo, Hardin and Massopust (GHM) [7].

The basic technique of balanced multiwavelet has

been evolved in many directions. One of the major

directions is balanced Multiwavelet system with

higher order balancing as reported by Lebrun and

Vetterli (BAT01, BAT02).[9] Yet another

interesting piece of work in this field is Orthogonal

Balanced Multiwavelet (BAT 01); [14] that has

great potential for denoising mammograms. The

present work synergizes the above mentioned

techniques viz. GHM, BAT01 and BAT 02, to pave

the benefits of accurate classification of

mammograms. The advantages of our

implementation are evident from the results

compared with the traditional Daubechies scalar

wavelet (D4) used for the same purpose.

4. Methodology Adopted

Our methodology comprises of the following

sequence of steps:

a. Scaling functions and wavelets for first

order balanced and order 2 balanced multiwavelets

are implemented in MATLAB.

b. The test mammograms for processing are

taken from images available at

http://www.cancer.org [10]

c. The test images are decomposed and

reconstructed using wavelet, Multiwavelet and

balanced multiwavelet systems mentioned earlier.

Analytical measures like mean square error (MSE),

root MSE, distortion, signal to noise ratio and

energy compaction ratio (ECR) are used for

experimentation.

d. Then test images are mixed deliberately

with Gaussian noise, using function available in

MATLAB [11]. These noisy images are

decomposed by wavelet, multiwavelets and

balanced multiwavelets.

e. Images are reconstructed using

approximate coefficients only. Analytical measures

mentioned in step 2 are calculated.

5. Balanced Multiwavelets

It is possible to design orthonormal linear phase FIR

filter systems to construct multiwavelets. However,

prefiltering step turns out to be crucial when applied

to scalar valued data. To avoid prefiltering, concept

of balancing is introduced in [15] which is extended

to higher orders in [9]. Using these results, we have

constructed orthonormal multiwavelets of order 1

using filter coefficients shown in table I. Figure 1

and figure 2 show scaling and wavelets constructed

using these coefficients. In first order balanced

multiwavelet, scaling function is flipped around 1

and wavelets are symmetric / antisymmetric, the

length is three tap (2 X 2). In order 2 balanced

multiwavelet, scaling function is flipped around 2

and wavelets are again symmetris / antisymmetric,

the length is five taps (2 X 2).

Figure 1. BAT01 scaling function and wavelets

http://www.cancer.org/



3

Figure 2. BAT02 scaling function and wavelet

Table 1. Coefficients of BAT01

Hk Gk k=0

0 2+√7

0 2+√7

0

-2

0

1 k=1 3 1

1 3 2 2

-√7 √7 k=2

2-√7 0

2+√7 0

-2 0

-1 0 factor 1/4√2 1/4

6 Metrics Defined In order to characterize the performance of the

system, certain benchmarking parameters are

required. This section formally defines all such

parameters. 5.1 Mean square error (mse)

[

( )]∑∑( ( ) ( ( ))

where S(x,y) is original mammogram image and

S‟(x,y) is denoised mammogram image.

5.2 RMSE = square root of MSE

∑∑( ( ) ( ( ))

5.3 Distortion = ∑ ∑ ( )

5.4 SNR = 1 / Distortion

5.5 ECR is defined as

ECR = ∑ ∑ ( )

∑ ∑ ( )

where S(x,y) is coefficient matrix of mammogram

consisting of approximate and detail coefficients,

and S^(x,y) is coefficient matrix with approximate

coefficients equal to zero.

5.6 Correlation as defined in MATLAB using

function corr2( ).

7 Results and Discussion

Figures 3 to 12 reveals the wavelet, Multiwavelet

and balanced multiwavelet based processing of

mammogram image. Figure 3 shows original

mammogram showing micro calcification. This

mammogram is decomposed and reconstructed

using D4 wavelet and multiwavelets as shown in

figures 4, 5, 6 and 7. Table 2 shows statistical results

obtained from these images. These results and

figures clearly indicate the superiority of the

balanced multiwavelets over the other wavelets for

accurate classification of mammograms. Energy

compaction ratio (ECR) also portrays more

information concentrated in low pass part of

Multiwavelet transform than in the low pass part of

wavelet transform as seen from table 2. Original

mammogram image is deliberately added with

Gaussian noise of mean average value zero, to create

noisy image as shown in figure 8. The subsequent

processed denoised images are shown in figures 9, 10,

11 and 12.

Figure 3. Original mammogram Figure


4

Figure 4. Mammogram reconstructed by D4

wavelet

Figure 5. Mammogram reconstructed by

GHM multiwavelet


BAT01 multiwavelet


BAT02 multiwavelet

Figure 8. Noisy mammogram

Table 2. Statistical results of

decomposition and reconstruction of image

Statistical

Measures D4 GHM BAT 01

BAT 02

MSE 9.0193 3.8018 3.6238 3.3454

RMSE 3.003 1.949 1.9036 1.829

Distortion 0.0039 0.0016 0.0015 0.0013

SNR 256.106 607.5764 666.676 769.237

Correlatio 0.9967 0.9986 0.9987 0.9991

ECR 0.0039 0.002 0.0036 0.0039

Figure 9. Denoised mammogram by D4

wavelet

Figure 10. Denoised mammogram by GHM

multiwavelet


5

Figure 11. Denoised mammogram by BAT01

multiwavelet

Figure 12. Denoised mammogram by

BAT02 multiwavelet

8 Conclusion

After reviewing recent emergence of multiwavelets,

we have examined the possibility of multiwavelets

in mammogram image processing, especially for

denoising application. We used simple method of

decomposition – reconstruction of image using

wavelet and multiwavelet transform to verify the

superiority of balanced multiwavelets. From above

results, it is seen that balanced Multiwavelets have

been proved to be superior to other wavelets, both

numerically and subjectively. Visually Multiwavelet

schemes seemed to preserve the edge better and

reduce Cartesian artifacts present in scalar wavelet

denoising. This work perhaps might be possibly

extended further in which other multiwavelets could

be applied to mammogram images to find out most

suitable multiwavelet for a particular mammogram.

References

[1] Gilbert Strang, “Short wavelets and matrix

dilation equations” IEEE transactions on

signal processing, vol. 43, No. 1, pp. 108-

115, January 1995.

[2] Woods, K.S.,et.al. “Comparative evaluation

of pattern recognition techniques for

detection of microcalcifications in

mammography”, International Journal of

Pattern Rece. and AI, vol 7, pp 1417-1436,

1993.

[3] Solka, J.L, et.al. “The detection of micro-

calcifications in mammographic images using

high dimensional features”, Proceedings of the

1994 IEEE seventh symposium on computer-

based medical systems, pp 139-145, 1994.

[4] Wan Mimi Diyana, et.al. “A comparison of

clustered microcalcifications automated

detection methods in digital mammogram”

IEEE ICASSP, pp. II385-388, 2003.

[5] Liyang Wei, et.al. “A study on several

machine-learning methods for classification of

malignant and benign clustered

microcalcifications” IEEE transactions on

medical imaging, vol. 24, no. 3, pp. 371-380,

March 2005.

[6] Ryohei Nakayama, et.al. “computer-aided

diagnosis scheme using a filter bank for

detection of microcalcification clusters in

mammograms”, IEEE transactions on

biomedical engineering, vol. 53, no. 2, pp. 273-

283, February 2006.

[7] J.S.Geonimo et.al. “Fractal functions and

wavelet expansions based on several scaling

functions”, J. Approx. Theory, vol. 78, pp. 373-

401, 1994

[8] C. K. Chui et. al. “A study of orthonormal

multiwavelets” J. Appl. Numer. Math., vol. 20,

pp. 272-298, 1996

[9] Jerome Lebrun, et. al. “High order balanced

multiwavelets: Teory, factorization, and

design”, IEEE transactions on signal

processing, vol. 49, no. 9, pp. 1918-1930,

September 2001

[10] Images of the breast cancer URL:

http://www.cancer.org Retrieved on February

14, 2009.

[11] MATLAB Version6.5, image processing

toolbox>functions

[12] Vasily Strela et. al. “The application of

multiwavelet filterbanks to image processing”,

IEEE transactions on image processing, vol. 8,

no. 4, pp. 548-563, April 1999

[13] D. M. Garge et. Al. “A Low Cost Wavelet

based Mammogram Image Processing for Early

Detection of Breast Cancer”, submitted to

Journal of Indian Science and Technology,

December, 2008

[14] Jian-ao Lian et. al “Balanced

multiwavelets with short filters”, IEEE signal

processing letters, vol 11, no. 2, pp 75 – 78,

February 2004

[15] Jerome Lebrun, et. al. “Balanced

multiwavelets: Teory and design”, IEEE

transactions on signal processing, vol. 46, no.

4, pp. 1119-1125, April 1998




6

Origin Authentication of Digitally Signed

Message Using Joint Signature Scheme in

Mobile Commerce

Aihab Khan, Malik.Sikandar Hayat Khiyal, Sara Ayub [email protected], [email protected], [email protected]

Abstract—In this era of advanced technology, mobile

commerce has become popular due to rapid growth of

communication technology but this requires

maintaining secure communication and protection

from threats. In this paper, we presented a

mechanism for secure and authentic communication

in mobile commerce based on joint signature scheme.

We formulate this technique for the authentication of

message originator who signs the message to buy a

product online through its mobile operator. Proposed

technique is efficient in mobile domain because it is

less computative and can be used with limited

resources in mobile commerce. An experimental

analysis shows that proposed technique overcomes

the major drawbacks of traditional digital signed

message, such as computational load, communication

load, complexity, public key operations, transaction

etc.

Keywords—Joint signature, M-commerce, Origin

Authentication.

1. Introduction

The technology grows faster and faster, much

advancement is done in information technology

regarding communication, security, privacy etc. A

mobile device is a wireless communication tool,

including mobile phones, PDAs, wireless tablets,

and mobile computers. Mobile commerce (M-

commerce) can be defined as any electronic

transaction or information interaction conducted

using a mobile device and mobile networks, which

leads to transfer of real or perceived value in

exchange for information, services, or goods. M-

commerce offers consumers convenience and

flexibility of mobile services anytime and at any

place, and is playing an increasingly important role

in payments and banking [7].

Mobile communication is one of the prime aspects

of telecommunication and this aspect turns into

mobile commerce due to rapid growth of internet

and digital technology. Security in mobile

commerce is vital for its widespread usage.

Encryption/decryption techniques, digital signature

algorithms and other security measures are being

develop to secure the m-commerce channel.

Authentication is a process to identify a mobile

user, in order to authorize him/her to use system re-

sources for specified purposes. Authentication

involves negotiating secret credentials between

prover, and verifier for protecting communications

[1].Digital authentication systems become an

essential part of electronic payments via public

networks. These systems allow people and

organizations to electronically certify the

authenticity of an electronic document etc. Policies

associated with these systems, raise important

privacy and protection issues.

Digital signatures are based on certain types of

encryption policies to ensure authentication.

Encryption is the process of encoding data that one

computer is sending to another, into a form that

only the other computer will be able to decode [4].

Security is a crucial requirement of an m-

commerce system due to the fact that the sensitive

financial information that these systems transmit

travel over untrusted networks where it is

essentially fair game for anyone with local or even

remote access to any part of the path followed [5].

Joint signature scheme used in mobile commerce

for the secure transactions but it is not costly and

computationally low. Joint signature scheme is

based on hash functions and encryption/decryption

algorithms to produce joint signature with message

originator and message signer and also to

authenticate the message originator for message

signer and vendor (message verifier).This

technique is new and not much work is done in this

technique yet. Li-Sha HE et al[3] proposed joint

signature scheme for the authentication of mobile

user, but this technique is not implemented yet and

also its results are hypothetical [3]. We have

worked out on this technique and implement it for

the authentication of mobile user by its network

operator and vendor.

This paper is organized as follows. Section 2

elaborates related work and state of the art today.

Section 3 provides the frame work overview of the

proposed model. Section 4 discusses the technique

of the research model. Performance parameters are

discussed in Section 5 and Section 6 consist of

Conclusion and future work of this research.




7

In this paper we introduce a joint signature scheme

for the authentication of Mobile user in M-

commerce. Major contributions are as follows:

- To formulate an algorithm for authentication of

the origin of the message sent from a mobile user

so as to prevent any fraudulent actions by the

vendor or any other entities.

- To develop a model for authentication of the

signature of the signer that has sent a message.

- To ensure that the content of the message are

authentic and are being sent from the mobile user.

2. Related Work

Joint signature scheme is proposed by Li-Sha HE et

al [3] in 2004 ACM Symposium on Applied

Computing. This technique overcome the security

issues related to m-commerce e.g. authentication,

non-repudiation, confidentiality, integrity etc.But

this technique was not implemented at that time, so

we took this scheme as a base for the authentication

of origin of digitally signed message by the mobile

user for purchasing goods online. Very few works

is previously done for the authentication but

techniques which have been used for the

authentication have several drawbacks. Also these

techniques were based on traditional digital

signature scheme like Diffie Helmen which has

drawbacks in limited resources of mobile domain.

Server-aided technique proposed by Chin-Ling

Chen et al [7] for the mobile commerce uses trusted

proxy server to co-ordinate transactions between

user and vendor. It is based on the Diffie Helmen

scheme and involves the one-time password

mechanism to establish session key in advance

between user and vendor with the help of trusted

proxy server. This technique is divided into two

phases; negotiation phase and authentication phase.

This technique discussed different aspects of

security issues like anonymity due to high

communication load involves in negotiation and in

authentication phase communication between

mobile user and trusted third party.

Another technique proposed by Wooseok Ham et

al [6] secure one way payment system in mobile

commerce. This technique uses two modular

multiplications, one modular inverse and the

second is hashing by the user using two public key

pairs and keyed hash function for computation. In

this technique only unilateral communication is

sufficient between user and vendor to complete

payment. This technique has three main functions;

withdrawal, purchase and deposit. Also user does

not need to participate in deposit phase so

communication load and computation load is low

in this scheme. As more than one transaction is

involved so transaction overhead is present in this

scheme.

3. Framework Overview

The proposed framework for the authentication of

origin in mobile domain using joint signature

scheme is shown in figure 1.

Message

Originator (MO)

Message

Signer(MS)

Message

Verifier(MV)

Message

H (OAC)

H (OAC1)

Sign(Message,

H(OAC))

Key Distribution

Center

Shared

Secret Id

key K1

Shared

Secret Id

key K1 Shared

secret Id

key K2

Shared

secret Id

key K2

Secure

channel

Secure

channel

Secure

channel

Figure 1: Proposed Abstract model for origin authentication using joint signature scheme

In a proposed model as shown in fig 1, three main

entities are illustrated,

The message originator which is a mobile

station (MO).

Server run by the network operator signed

the message in its home environment(MS)

And service provider which verifies the

message and provides different services to

the mobile user (MV).

The shared keys are securely distributed between

these three entities. The message originator sends a

message along with H(OAC) and H(OAC1) to the

message signer which sign the message by its

private key and send it to the message verifier

which later on verifies the message and provide

authentication for the message originator.

The notations used in the model are given in table 1


8

Table 1: Notations

Notation Description

MO Message Originator

MS Message Signer

MV Message Verifier

H(OAC) Hash of Origin Authentication

Code between MO and MV

H(OAC1) Hash of Origin Authentication

Code between MO and MS

Id K1 Secret key shared between MO

and MV

Id K2 Secret key shared between MO

and MS

A detailed discussion of proposed abstract

model for origin authentication using joint

signature scheme is given in following section.

4. Technique

The abstract model of figure 1 elaborated by more

descriptive model is given below.

The Figure 2 explains as how message originator

MO produces the hash functions and sends it to the

message signer MS. Hash function H(OAC) and

H(OAC1) is produced on key Id K1 and Id K2

respectively, and message but with different keys

securely shared between these three entities.

Message signer MS signs the message and

produces the joint signature after verification of

message originator MO. After verification message

signer MS encrypts the message and sends it to

message verifier MV. Message verifier MV

decrypts the message and produces hash function

of its own and then after comparing both hash

functions provides the authenticity for the message

originator MO.

The process of origin authentication using joint

signature scheme consist of following four major

steps.

Step 1 :( Sharing Secret Key)

The message originator (MO) sends the message

and a shared secret key Id K1 to the message

verifier (MV) and produces a joint signature on

message with the help of message signer (MS) as

shown in fig 3.

M

Key

Distribution

center

Message

Originator(MO)

Message

Verifier(MV)

Secret

id K1

M

Secret

id K1

Secret

id K1

Figure 3: Distribution of secret keys between Message Originator and Message Verifier

M

M

----------

H(OAC)

----------

H(OAC1)H

H H(OAC)

H(OAC1)

llEp

Key

PRms

H(OAC)llH(OAC1)ll

M

Dp

Key

PUms

H(OAC)

--------

M

E(H(OAC)llM)

Id K2

Id K1

M H

Id K1

compare

Message

Originator(MO)

Message

Signer(MS)

Message

Verifier(MV)

------------------Joint Signature Generation---------------- ------Joint Signature Verification---------

H(OAC1)

H

compare

Secret

Id K1Secret

Id K2

Key

Distribution

Center

H(OAC)

Figure 2: Descriptive model of origin authentication using joint signature scheme


9

Step 2: (Produce Hash Function)

The message originator (MO) sends the message to

the message signer (MS) and produces a hash on

Origin Authentication Code H(OAC) and Origin

Authentication Code 1 H(OAC1) and sends it to

the MS with message. Also a Secret key Id K2 is

shared between MO and MS. Process is shown in

fig 4

M

H

H

ll

M

----------------

H(OAC)

----------------

H(OAC1)

H(OAC)

H(OAC1)

Key

Distribution

center

Message

Originator(MO)

Message

Signer(MS)

Secret

Id K2Secret

Id K1

Secret

Id K2

H

H(OAC1)

compare

Figure 4: Production of Hash function by Message Originator

The algorithm developed for producing hash

function is as follow:

Algorithm: Production of Hash function

Input: min, max, plaintext

Output: hash value

1.salt=random.next(min,max) //min and

max are integer values

2.plaintxtbytes=getbytes(plaintxt)

//converting from string to bytes

3.plaintxtwidsalt=plaintxtbytes+salt

//appending salt bytes

4. hash = SHA1 managed()

5.hashbytes= hash.computehash(plaintxtwidsalt)

//calculating hash value

6.hashvalue = convert.tobase64string(hashbytes)

//converting to string

Figure 5: Algorithm for producing hash function

Step 3: (Joint Signature Generation)

The message signer (MS) signed the message using

its private key on Hash Origin Authentication Code

H(OAC), a Hash Origin Authentication Code 1

H(OAC1) and message generated by the MO and

sends it to the MV as shown in fig 6.

Step 4 :( Origin Authentication)

The message Verifier (MV) decrypts the message

received from MS by public key of MS and verifies

the origin of the message by H (OAC) with the

help of message and shared secret key Id K1. And

MS verifies the H (OAC1) with the help of secret

key Id K2 shared between MO and MS.

The algorithm for the authentication of origin is

shown in Figure 7

Algorithm: Origin Authentication

Input: hash value

Output: verify hash for origin authentication

1.hashwidsaltbytes=convert.frombase64string(hash

value) // converting to bytes

2. if(hashwidsaltbytes.length < hashsizeinbytes) then

3. verify hash = false

4. end if

5. for I = 0 to saltbytes.lendth-1

//saltbytes is a difference between

//length of hashsizebits and hashsizebytes

6.saltbytes(I)= hashwidsaltbytes(hashsizeinbytes)

7. next I

8.expectedhash=computehash(plaintext,saltbytes)

// computing hash values to verify

9. verify hash = (hash value = expectedhash)

// comparing hash values

Figure 7: Algorithm for Origin Authentication

The above steps can also be elaborated sequentially

by using sequence diagram in fig 8 as:

M

------------------

H(OAC)

Ep

Key

PRms

H(OAC)llM

Dp

Key

PUms

HOAC

-----------------

M

E(H(OAC)llM)

Message

Signer(MS)

Message

Verifier(MV)

Figure 6: Joint signature generation by

Message Signer


10

Message Originator Message Signer Message Verifier

Sends shared secret key

k1

Send message to buy

Sends shared secret key

k2

Send message

Send hash of message

and its origin along with

message Verify hash of message by

k2

Encrypts the message and

hash of message origin by

own private key

Send encrypted message

Produce the hash on

given message by

using key

Verify the hash on

origin of message

with the produced

hash

Authenticate the Message Originator

Decrypt the

message by MS

public key

Figure 8: Sequence Diagram of working of model for Joint signature Origin Authentication

5. Performance Results

Performance of proposed technique is analyzed on

parameters like computational load,


11

communication load, complexity, public key

operations, transactions with respect to other

techniques and following observations were made.

Table 2: Performance measure of proposed Technique

Computational

Load

Joint Signature Scheme

(Proposed Scheme)

Server Aided Signature

Scheme

Secure one way mobile payment

Scheme

In this scheme two hash function and one public key

operation is used in

computation which is very efficient in limited resources

so computational load is Low in this scheme

Proxy server or trusted third party is

involved in this scheme which performs

complex operations, based on traditional digital signature scheme like Diffi

Helmen which bears more computational cost in limited resources

so computational load is High in this

scheme.

One modular inverse, two

modular multiplications and two

hash functions are involved in computation which can

effectively be implemented in

mobile domain with limited resources. Also no

exponentiation calculations are involved that are used in RSA

and a Diffi Helmen technique,

so computational load is Low.

Communication

Load

In this scheme only one

transaction is done from customer to the network

operator so communication

load is Low in this scheme.

Two way Communications are involved in negotiation phase and in

authentication phase so more than one

transaction is involved in this scheme so communication load is High in this

scheme.

In this scheme customer does not

need to be involved in deposit

phase, so unilateral communication is done between customer and

vendor to complete payment

transaction. So communication load is Low in this scheme

Complexity


public key operation is performed at service provider

to verify the joint signature

by network operator so public key operation is Low

in this scheme.

Two public key operations are involved in

this scheme, one to verify secret from original signer by public key of trusted

third party and second to verify signature

by public key of signature signer. So public key operations in this scheme is

High.

In this scheme customer has two

private and public key pairs for

signing and verification. So two public key operations are involved

in this scheme, so public key

operation is High in this scheme.

Transactions


transaction is required from

customer to network operator

so transaction in this scheme is Low

In this scheme two transactions are required

between original signer and signature signer in negotiation and authentication phase so

transaction in this scheme is High.

In this scheme more than one

transaction is required in

withdrawal, purchase and deposit

phase so transaction in this scheme is High.

Experimental analysis shows that joint signature is

much efficient and less complex than others

schemes with low computation and communication

load is which is very useful in mobile commerce as

in mobile commerce resources are very limited as

compare to other domains like banking, online

purchasing etc, so joint signature scheme is

efficient and can be used in mobile commerce for

origin or client authentication. The comparison is

shown in table 3.

Table 3: Comparison Analysis

Techniques Computational Load Communication Load Public key

operations Complexity Transactions

Joint Signature

scheme Low Low Low Low Low

Server-aided

Signature

Scheme

High High High High High

Secure One-way

Mobile Payment Low Low High Low High

Proposed

Scheme Low Low Low Low Low

6. Conclusion And Future Work


12

In this paper, we have presented a novel joint

signature scheme for the authentication of origin of

message that is digitally signed by the mobile user

(message originator) with the help of its network

operator(message signer),both jointly produce the

signature which is going to be verified by the

vendor(message verifier).Authentication is done on

both entities i.e. message signer and message

verifier which proved them that the message

originator is the right person who sends message to

vendor. Furthermore this technique is more

efficient than other traditional schemes which are

used for authentication in mobile commerce. In

comparison with existing techniques mainly server

aided scheme and secure one way mobile payment

mechanism, this technique overcomes all major

disadvantages of existing techniques.

In future, it is recommended to extend joint

signature scheme for the authentication of message

that is digitally signed by the user in order to avoid

any fraud over the transmission line. Moreover this

technique can be implemented for other security

issues like confidentiality, integrity, non-

repudiation etc.

References [1] Babu.S.B, Venkataram.P, 2009, “A Dynamic

Authentication Scheme for Mobile Transactions”, Protocol

Engineering Technology (PET) Unit, Department of Electrical

Communication Engineering Indian Institute of Science,

Bangalore, 560 012, India (Email: fbsb,

[email protected]) International Journal of Network Security, Vol.8, No.1, PP.59-74, Jan. 2009

[2] Chen C-L, Chen C-L, Liu L-C, Horang.G, 2007, “A Server-

aided Signature Scheme for Mobile Commerce”, Department

of Computer Science and Information Engineering, Chaoyang

University Technology,Taichung,[email protected], Department of Mechatronics Engineering, National Changhua

University of Education Changhua, Taiwan 500, ROC.

[email protected], Department of Computer Science, National Chung Hsing University , Taichung, Taiwan

402, [email protected], , Department of Computer

Science, National Chung Hsing University , Taichung, Taiwan 402, ROC. [email protected]. IWCMC'07, August 12-

16, 2007, Honolulu, Hawaii, USA.

[3] He L.S, Zhang.N,(2004), “A New Signature Scheme:

Joint-Signature”, Department of Computer Science the

University of Manchester, Manchester UK, 0044-161-2756270 {hel, nzhang}@cs.man..ac.uk, SAC’2004, March 14-17, 2004,

Nicosia, Cyprus.

[4] Kadhiwal.S, Usman.M.A, 2007, “Analysis of mobile

payment security measures and different standards”,

Shaheed Zulfiquar Ali Bhutto Institute of Science and Technology, Karachi, Pakistan.

[5] Kritzinger.F, Truter.D,(2003) , “A Secure End-to-End

System for M Commerce: Research Paper CS03-24-00”, October 12, 2003.

[6] Ham.W, Choi.H, Xie.Y, Lee,M, Kim.K, „Secure One-way

Mobile Payment System Keeping Low Computation in

Mobile Devices‟, International Research center for Information Security (IRIS) Information and Communications University

(ICU) 58-4 Hwaam-dong, Yusong-gu, Daejeon, 305-732, S.

Korea, School of management Information and

Communications University (ICU).

[7] Nambiar.S, Lu.C-T, Liang.L.R, 2008 “Analysis of Payment

Transaction Security in Mobile Commerce‟, Department of Computer Science Virginia Polytechnic Institute and State

University 7054 Haycock Road, Falls Church, VA 22043

{snambiar, ctlu}@vt.edu, Department of Computer Science University of the District of Columbia Washigton, DC 2008,

[email protected].





mailto:nzhang%[email protected]

mailto:ctlu%[email protected]


13

Non Repudiation in M- Commerce Using

Joint Signature Scheme

Aihab Khan, Malik Sikandar Hayat Khiyal, Madiha Tariq

[email protected], [email protected]

Abstract—Being the hottest issue of today’s time there

as a lot of work to be done on mobile commerce .in

mobile commerce mobile is used to avail a lot of

services. One of these services includes online

purchasing of different items. Mobile subscribers can

by items anywhere at any time by using their mobile.

The bills are compensated by their network operators.

Different security issues are involved during such

transactions. One of the issues that of non-

repudiation. This service prevents the sender and

receiver to deny their participation in the transaction

and to ensure the integrity of the message. This paper

represents the mechanism for non-repudiation in m-

commerce using joint signatures. This mechanism is

based on the use of hash functions and traditional

digital signatures where network operators have

trusted third party or an arbitrator to satisfy this

requirement. This mechanism is efficient to be used in

mobile domain having less resource due to low

computation and communication load. Also it is

simpler than traditional digital signature scheme. We

formulate this approach to overcome the problem of

non-repudiation in mobile domain.

Keywords—Authentication, Joint Signatures, Mobile

commerce, Non-repudiation.

1. Introduction

Internet is used to share information along different

channel. This information is shared along multiple

channels through internet protocol security

(TCP/IP).Network security consists of several

provisions in computer network infrastructure,

policies to protect their network from illegitimate

user and continuous monitoring of network.

1.1 M-Commerce verses E-Commerce

M-commerce is unique from e-commerce having a

show function. There are some similarities between

m-commerce and e-commerce but as a whole m-

commerce is different from e-commerce.

“Mobile commerce is any transaction, involving

the transfer of ownership or rights to use goods and

services, which is in initiated and/or completed by

using mobile access to computer-mediated

networks with the help of an electronic device.”

When data is travelling over the network it needs to

be protected. A lot of security features should be

incorporated for the secure m-commerce for

security reasons a lot of techniques like digital

signatures, hash functions, encryption etc. are used.

Digital signature is a type of asymmetric

cryptography. It helps the receiver to make sure that

message is send from legitimate users.

1.2 Digital Signatures in m-communication

Existing digital signature schemes are costly to be

used in m-commerce. Digital signature generation

is most time and resource consuming operation to

be performed by mobile devices. Different

asymmetrical payment methods have been

developed for mobile users to buy goods online.

These methods require less resource to perform the

transactions but there is a major problem with these

approaches that network operator may abuse the

trusts. Therefore these approaches must be outfitted

with a strong security level so that everyone

involved in the transactions should be accountable.

As digital signature generation is computationally

expensive for a mobile device, which has

considerably less computing resources then a

desktop, so another scheme may b used i.e. joint

signature scheme [7].The model presented in this

paper is derived from the research work of Li-Sha

HE et al that was presented in ACM Symposium on

Applied Computing in 2004.in there research they

have presented a model for implementing joint

signature schemes in m-commerce. Here three

entities are involved. The originator generates the

message and applies hash on message with shared

secret id key K1 and K2 and sends the message

along with two hash values (joint signatures) to the

signer. The signer signs the joint signature with its

private key and sends this signed joint signature to

the verifier where verifier decrypts to authenticate

the origin this model is a hypothetical model that is

not implemented. Our research is based on the

implementation of this model along with addition



14

of some security services may have developed a

mechanism for implementing non-repudiation of

both sender and receiver in m-commerce using

signature scheme and incorporated our mechanism

to their hypothetical model and also implemented

there model. This research is intended for

implementing non-repudiation in m-commerce

using joint scheme. Objective of this research is to

develop a mechanism for non-repudiation in m-

commerce scheme. This mechanism caters the

prevention of denial from sender and receiver about

their participation in the transactions and ensures

the integrity of the message. The proposed

mechanism is applicable in mobile domain with

limited resources. The reminder of this paper is

organized as .In section 2 named as ‘Related Work’

brief discussion of different signature scheme is

represented. In the section 3 ‘Proposed Framework

Model’. Our proposed model is described. The

explanation of our proposed model is given in

section 4 ‘Technical Description of Proposed

Model’. In the section 5 ‘Performance Results’ the

performance of our proposed mechanism is

discussed. Section 6 as conclusion is followed by

the ‘Future Work’

2. Related Work

In this section we introduce three important

signature schemes proposed by Li Sha HE et al [1],

Ching-ling Chen et al[2] and Guilin Wang et

al[3].Joint signature scheme [1] is an extension of

digital signature scheme as this scheme is based on

the use of hash functions and traditional digital

signatures. In joint signature scheme there is no

concept of proxy signer and only one public key

operation is involved so there is less

communication and computational overhead. In

mobile domain there are limited resources so this

scheme is efficient to be used in mobile domain.

Digital signature scheme is used where there is

large number of resources hence on mobile domain

with limited resources using digital signature

scheme is not that much efficient. Server aided

signature scheme [2] involves hash functions and

traditional digital signature scheme. Here signature

server is required, signature server and original

signer require a round trip-communication.

Signature server verifies the signature on received

public key. In this technique there is a computation

and communication overhead for signature

generation. Hence time required to generate a

signature is increased. Due to all these reasons this

technique is not efficient to be used in mobile

domain. In proxy signature scheme [3] the proxy

signer is introduce to produce a digital signature on

behalf of the original signer. Proxy signature

scheme has three categories named as full

delegation, partial delegation and delegation by

warrant. In full delegation the proxy signer signs

the message with original signer keys, in partial

delegation new proxy key is generated from the

original key by the original signer and sent to the

proxy signer. Proxy signer then uses this proxy key

for purpose of signature generation. In delegation

by warrant there is higher processing overhead as

original signer has to sign certificate with its private

key. This scheme also has higher processing

overhead and high communication and computation

load. In this paper we introduce several security

services as authentication, message integrity, and

non- repudiation in m-commerce to a scheme

named as joint signature scheme. Other security

services like confidentiality etc can also be

implemented using this scheme.

3. Proposed Framework Model

Key Distribution

Center

Network operator

(NO)Message sender

(S)

Service Provider

(SP)

Secure channel Secure channel

Secure channel

Shared id key K1

Shared id key K2Shared id key

K1

Shared id key K2

Message

HOACSSP

HOACSNO

Sign message

HOACSSP

HOACSNO

HOACSSP

Figure 1: Framework Model

The proposed framework model shown in fig 1

explains that key distribution center distributes the

key with the message sender(S), network operator

(NO) and the service provider(SP).message

sender(MS) sends a message, compute hash of it by

using shared key and send it to NO.NO signs the

message, verifies it, and send it to SP.SP then

verifies that non repudiation is not occurring by

using its shared key.

Description of the terms involved in proposed

model are given below:


15

Table 1 Notations

S Message sender

NO Network operator

SP Service provider

M Message being sent by the message

sender

K1 Shared id key between message

sender and network operator

K2 Shared id key between message

sender and service provider

H Used for hash function

|| Sign of concatenation

PRNO Private key of network operator

PUNO Public key of network operator

HOACSSP

Hash origin authentication code

between sender and service

provider

HOACSNO

Hash origin authentication code

between sender and network

operator

EP Public key encryption

DP Public key decryption

4. Technical Description of Proposed Model

Technical description of the proposed model Is

given below:

Step 1:

The message sender(S) sends the message to

service provider (SP) and produce a joint signature

on message with the help of network operator.

(NO)

Step 2:

The network operator (NO) signs the message

using its private key on hash origin authentication

code between sender and service provider

HOACSSP, a hash origin=n authentication code

between sender and network operator (HOACSNO)

and message, NO will also verify the hash function

in order to verify that the message is actually sent

from the legitimate sender i.e. origin authentication.

Also it verifies HOACSNO for the sake of message

integrity and origin authentication. Once the origin

is authenticated it cannot deny its participation in

the transaction. It is done for the non-repudiation of

the origin.

Step 3:

The service provider (SP) decrypts the message

Figure 2 :Proposed Model


16

using NO’s public key to authenticate the network

operator. Network operator cannot deny its

participation in the transaction. Also it verifies the

message for the message integrity by comparing the

message from NO to the message sent by the

sender. SP will also verify hash function in order to

verify that the message is actually sent from the

legitimate sender .i.e. origin authentication.

Step 4:

The service provider (SP) after receiving

HOACSSP from the network operator (NO) will

send it back to the NO in order to get authenticated

by the network operator. Once the SP is

authenticated it cannot deny its participation in the

transaction. It is done for the non-repudiation of the

receiver.

In the above shown fig 2, message sender (MS)

sends a message, compute hash by using keys, and

then concatenated message to these is send to NO.

Till here joint signature is generated. Then NO

encrypts

This concatenated message by using its private key.

At SP end this encrypted message along with hash

is decrypted by using public key of No. At SP end

the original message and hashes i.e HOACSNO and

HOACSSP is compared to verify non repudiation

Step 1 (sharing secret key)

Key distribution center distributes the secret shared

id key K1 and secret shared key K2 among the

message sender (S),network operator(NO) and the

service provider.K1 and K2 are sent to the message

sender through a secure channel also K1 is sent to

the NO and K2 is sent to the SP through secure

channel by key distribution center. This is shown in

fig 3.

Step 2 (Message Generation)

Message sender generates the message and sends

this message to the service provider (SP) as well as

network operator (NO).

Step 3 (Production of hash on Message)

The message sender (S) generates message and

produces HOACSNO, Hash Origin Authentication

code between the sender and network operator and

HOACSSP. Hash origin authentication code

between sender and service provider with the help

of shared secret key K1 and K2 respectively on

message and sends both HOACSSP and

HOACSNO to the network operator (NO) as shown

in fig 4.

Step 4 (Joint Signature Generation)

Figure 3

Figure 4


17

The network operator (NO) signs the message

using its private key on HOACSSP, HOACSNO

and message generated by the S and sends it to the

Service provider (SP).this shown in fig 5.

Start

end

Message ||

HOACSSP ||

HOACSNO

received

Send encrypted

message to the

other server

Encrypt using

its private key

Figure 5

Step 5(Authentication)

The service provider (SP) decrypts the message

received from NO by public key of NO and verifies

the origin of the message by HOACSSP with the

help of message and shared secret id key K1.this is

done on order to cater the non-repudiation of origin.

NO verifies the HOACSNO with the help of shared

secret id key K2 between S and NO as shown in fig

6.

Start

end

Encrypt

Message ||

HOACSSP ||

HOACSNO

received

Decrypt using the

other server’s

public key

Figure 6

Step 6(Non-Repudiation)

The service provider (SP) when decrypts the

message that is sent from NO gets HOACSSP.SP

sends this HOACSSP back to the NO for the

purpose of its authentication. This is a concept on

hand shaking which is implemented in order to

cater the non-repudiation of receiver. This is shown

in fig 7.

start

end

Send HOACSSP

to network

Operator

Verification by

network

operator

Service

provider

Authenticated

Figure 7

5. Performance Results

The results demonstrate that joint signatures cam be

efficiently used in m–commerce.

Computational load

In proposed scheme two hash functions are used for

computation, and hash function can easily

implement in mobile domain with limited resources

so in proposed scheme computational load is low.

Communication Load

In propose scheme only one transaction is required

from message originator to message signer for

producing joint signature so in proposed scheme

communication load is low.

Public key operations

In proposed scheme only one public key operation

is required by message verifier to verify the joint

signature from message signer. So in proposed

scheme public key operation is low.


18

Complexity

In proposed scheme trusted third party is no

involved (NO is behaving as a trusted third party)

in communication so proposed scheme is less

complex than other schemes.

Transactions

In proposed scheme one transaction is done

between message originator and message signer for

producing joint signature scheme so in proposed

scheme transaction overhead is low. Thus joint

signature scheme is much efficient and less

complex than other scheme, in joint signature

scheme computation and communication load is

low which very useful in mobile commerce as

resources are limited in mobile domain as compare

to other domains like banking, online purchasing

etc, so joint signature scheme is easy and effective

and can be used in mobile commerce for

authentication non-repudiation and message

integrity.

6. Conclusion and Future Work

In this paper we have presented a mechanism for

non-repudiation in m-commerce using joint

signature scheme. In situations where there is not

complete trust between sender and receiver

something more than authentication is needed.

Basically it is the need of non-repudiation. The

mechanism that we have presented is a type of

arbitrated digital signature. Our mechanism gives

an efficient solution to the problem of repudiation.

In order to make the transactions securer inclusion

of this feature is very important. The reason due to

which we selected joint signatures for

implementing non-repudiation in m-commerce is

that in mobile domain we have limited resources.

Joint signature scheme best fits in the domain

having fewer resources. Also this scheme is more

efficient than the existing scheme as it involve less

public key operations and transactions. Due to this

reason the scheme is simpler and less expensive.

For future we’ve planned to work on other security

issues like confidentiality etc. to incorporate in this

scheme.

References

[1] Li-Sha He, Ning Zhang, "An Asymmetric

Authentication Protocol for M-Commerce

Applications," Eighth IEEE Symposium on

Computers and Communications, ISCC, pp.244,

2003

[2]Ching Ling Chen et al ‘A Server-aided

Signature Scheme for mobile commerce’,

Department of Computer Science and Information

Engineering, Chaoyang University of

Technology,Taichung,2007,[email protected].

edu.tw

[3]Guilin Wang et al ‘Proxy Signature Scheme

with Multiple Original Signer for Wireless E-

Commerce Applications’, Infocomm Security

Department, Institute for Infocomm Research

(I2R),2004

[4]Chung et al ‘Adaptation of proxy certificates

to non-repudiation protocol of agent-based

mobile payment systems’, Springer Science

Business Media, LLC 2007

[5]Chin et al ‘A fair and secure mobile agent

environment based on blind signature and proxy

host’, Department on Computer Science and

Information Management, Providence University,

Department of Computer Science and Information

Engineering National Chung Cheng

University,2004

[6] Jonker ‘M-commerce and M-payment

combining technologies’, 2003

[7] http://en.wikipedia.org/wiki/Mobile_commerce

http://en.wikipedia.org/wiki/Mobile_commerce


19

Design Issues and Applications of Wireless

Body Area Sensor Networks

1Rakhshanda Yousaf,

2Sajjad A Madini

3Aihab Khan

1,2Comsats Institute of Information Technology, Abbottabad, Pakistan

3Fatima Jinnah Women University, Rawalpindi, Pakistan

[email protected], [email protected], [email protected]

Abstract— A body area network connects together

different nodes attached to human body and then to

an external station and sometimes to internet.

Different network topologies are used according to

the requirement of application. Wireless body area

networks offer many promising new applications in

the area of remote health monitoring, sports, and

military etc. BANs are faced with many research

challenges as this area is still thought of being in its

infancy. These challenges include channel mode

selection, antenna design, physical and MAC layer

protocol design, and many more. Bluetooth, Zigbee,

ANT, Sensium, Zarlink etc are some of the candidate

wireless technologies that conform to the needs of

BANs. Conflicts between requirements of BANs also

need to be addressed, these conflicts exist among

requirements like security, efficiency, safety etc.

Continuous monitoring of wireless users is very

important because they may get stuck in any critical

condition. This work address all these issues in detail.

Keywords— body area networks (BANs), body sensor

networks (BSNs), wireless body area networks (WBANs),

wireless networks, wireless sensor networks (WSNs).

1. Introduction

A Body Area Network is formally defined by IEEE

802.15 as, "a communication standard optimized

for low power devices and operation on, in or

around the human body (but not limited to humans)

to serve a variety of applications including medical,

consumer electronics / personal entertainment and

other" [IEEE 802.15].The term BANs will be used

as shorthand for body area networks in the rest of

text.

A body area network connects self-regulating

nodes attached to the body surface, implanted in

the body, or embedded in the clothing for

applications in health care, sports, entertainment,

military, pervasive computing and many other

areas [5]. The nodes in a BAN can be implanted

medical devices, sensors such as ECG electrodes,

activity sensors, data storage etc [9].

Low-power integrated circuits, ultra-low-power RF

technology, wireless communications, and energy

harvesting and storage have gone through many

technological advances which has enabled the

design of lightweight, low-cost, tiny, and

intelligent medical devices, sensors and networking

platforms. With these achievements the concept of

pervasive wireless networks seems to become a

reality in near future [6].

The recent bang of BANs took years of research

and progress in the field of wireless sensor

networks (WSNs), although, the technologies as

well as the development of BANs can be mapped

back to several decades. Plenty of tiny yet powerful

sensor platforms have been demonstrated for

various ubiquitous applications in the past decade.

A BAN is also a type of wireless sensor network,

but it specifically deals with the challenges

associated with monitoring of human body as well

as the interaction of human body with

environments. These challenges are exceptional

because of human body’s complex internal

atmosphere and the individual attributes of human

body that respond to and interact with the outside

world [5].

There are different classifications for BANs based

on whether the devices supported by BANs are

invasive or noninvasive. Invasive wireless body

area networks support in-body communication and

the two-way communication between entrenched

medical devices and the external base stations,

while noninvasive wireless body area networks

support communication among other noninvasive

sensors on or close to the human body and the

surroundings [8].

In this paper, an outlook or survey on applications

and design issues of body area sensor networks is

presented. The rest of the paper is organized as

follows. Section 2 describes the system architecture

of BANs. Applications areas are discussed in

section 3, while section 4 covers the key research

challenges associated with BANs. Section 5

contains overview of candidate wireless

technologies for BANs. In section 6, some practical

issues and relations between different requirements

of BANs are discussed and Section 8 addresses the

issue of positioning of a BAN user. In the end, a

conclusion of all the discussion is presented.

http://www1.cse.wustl.edu/~jain/cse574-08/ftp/ban/index.html#IEEE802.15


20

2. System Architecture /Network

Topologies

In [2], Mark et al have discussed system

architecture and network topologies associated with

BANs. BANs can be organized into different

network topologies based on the application design

choice. Most common network topologies include;

Point-to-point network, where two devices are

connected directly; Star network, where all devices

are connected to a central node or a master node

and communication between two slave nodes

requires passing all packets through the master

node; Mesh network, where any pair of devices can

communicate with each other directly as long as

they are within each other’s radio range; Star-mesh

hybrid network, where a mixed star and mesh

network provides the advantage of simplicity of a

star topology and the flexibility of a mesh

topology; and Cluster tree network, where the mesh

topology is organized to provide a single path

between two devices to reduce the routing

complexity.

Each topology presents its specific set of

advantages and drawbacks regarding network

characteristics such as latency, robustness,

capacity, and the complexity of data routing,

processing, and power consumption. Depending on

the application scenario, BANs with different

topologies are employed either in a standalone

context or in combination of mobile devices (e.g.,

mobile phones) or ambient sensor networks [2].

A stand-alone body area network consists of small

wireless nodes in, on, or in the immediate

neighborhood of the subject. Internet Connected

BANs is a situation where a stand-alone BAN is

connected to the Internet by means of a mobile

base station. The base station acts as a connection

between the BAN subject and the Internet service

provider. The BAN observes, gathers, and stores

data. Collected raw data or locally processed data

can be forwarded via the base station and the

Internet to the service providers (e.g., healthcare

providers, personal trainers, etc.) in real-time if

necessary. The base station server acts not only as

an intermediary between different communication

technologies but also as the protocol gateway

between the BAN, the Internet, and the service

providers [2].

A futuristic scenario is a world with imperceptible

pervasive sensing throughout the environments in

which people live and interact with it. The

architecture of this system will be such that people

are transparently absorbed in the system where

BANs are incorporated like a dream with the global

environments. Subjects of BANs travel within this

pervasive sensing environment to obtain a variety

of services e.g., medical, entertainment, etc.

Handoffs due to mobility are also transparent. The

large amount of data collected through the

pervasive sensing can also be utilized for

knowledge discovery through data mining, pattern

recognition, and machine learning [2].

3. Application Areas

In [2, 8, and 12], different application areas of

BANs are discussed which are summarized here.

Due to various components of BANs that can be

connected and integrated, body area networks are

supposed to be able to provide various functions in

healthcare, emergency, work, research, lifestyle,

sports, or military.

Healthcare: BANs can be used to connect

various devices including digital spectacles and

hearing aids, and will not be restricted to in-home

patient monitoring but will also involve trauma

care, chronic disease research, pharmaceutical

research, and remote assistance in cases of

accidents where mobile devices can be used to

communicate with the hospital and to send data

from the ambulance to alert the concerned

authorities and to get information about providing

first aid to save victim’s life [2].

BANs allow monitoring of patients’ medical status

by sensing and transmitting measurements such as

blood pressure, heart rate, ECG, respiratory rate,

body temperature, chest sounds, etc. Diagnostic

devices can be used to pervasively monitor a

patient’s physical and biochemical parameters

continuously in any environment. Particularly

speaking, BANs can be mainly important for

diagnosis and treatment of patients with chronic

disease, such as hypertension, and diabetes, etc.

BANs are also beneficial to hospital patients who

receive monitoring at different levels for e.g.,

pervasive monitoring of patients in the hospital no

matter where they are, pervasive in-patient

monitoring through implanted devices that enables

medical staff to predict, diagnose, and start

treatment before the patient reaches to adverse

stage of disease [8].

BANs are also highly beneficial for monitoring and

assistance of elderly people, as more and more

people demand a better quality of life. Eventually,

BANs offer a great potential to build up a

personalized healthcare system where cure may be

provided to the patient at the monitoring level,

detection and diagnosis level [10].

In [10], M. Corchado et al, have presented a

distributed telemonitoring system, aimed at

improving healthcare and assistance to dependent


21

people at their homes. The system implements a

service-oriented architecture based platform, which

allows heterogeneous wireless sensor networks to

communicate in a distributed way independent of

time and location restrictions. This approach

provides the system with a higher ability to recover

from errors and a better flexibility to change their

behavior at execution time.

Work and Emergency Services: BANs can

also be used to provide services for first responders

such as an intelligent fire, safety, and rescue

system. Using tiny wireless sensors, the system

monitors the condition and location of firefighters.

The sensors can pass on vital information to an

incident commander, who is coordinating a team

from outside the building.

Lifestyle and Sports: BANs enable new

services and functions for wireless body-centric

networks including wearable entertainment

systems, navigation support in the car or while

walking, museum or city guide, heart rate and

performance monitoring in sports, infant

monitoring etc.

Military: A battle dress uniform integrated with

a BAN may become a wearable electronic network

that connects devices such as life support sensors,

cameras, RF and personal PDAs, health monitoring

GPS, and transports data to and from the soldier’s

wearable computer. As a result, BANs provide new

opportunities for battlefield lethality and

survivability.

It is envisioned that wireless body area networks

will become a key component of the future Internet

and serve as an vital vehicle for information access

and exchange in supporting better healthcare,

education, and lifestyle.

4. Research Challenges

In [1, 8, and 12] different challenges associated

with BANs are presented. BAN brings forward a

number of research issues that need to be

considered in the design of radio frequency (RF)

wireless systems.

Users carry several BAN devices globally such as

hearing aids etc; hence, BAN radio is required to

operate worldwide. There is abundance of high

power technologies in ISM bands and they have

cast a degradation effect on the low-power BAN

devices which thus makes them less appealing for

high fidelity medical applications. WMTS bands

are heavily used but their use is restricted to

healthcare facilities in the United States. UWB can

be exploited for wearable applications but it raises

the issue of coexistence with high-data-rate

multimedia applications [12]. The rules for

MedRadio wing band are very strict and limiting.

These issues have provoked the FCC to think about

opening up 2360–2400 MHz range for medical

BANs. This is planned to hold up wideband

entrenched micro-stimulator devices that can serve

as an artificial nervous system to reinstate

sensation, mobility, and function to paralyzed limbs

and organs [1].

Another issue is regarding the channel model.

Channel model plays a vital role in the design of

PHY technologies. Experimental channel modeling

for embedded and wearable devices is hard because

humans and healthcare facilities are involved and

both are governed by regulations.

Antenna design for body area networks is yet

another challenging issue due to limitations on the

size, stuff, and form of the antenna [3]. Only non-

caustic and biocompatible material such as

platinum or titanium can be used for implants,

which results in poorer performance when

compared to a copper antenna. Organ and location

of antenna decides its shape and size which further

restricts the choice of designer [1].

Physical layer protocol design requires reducing

power consumption without affecting reliability.

Flawless connectivity should be maintained in

dynamic environments with the slightest possible

performance degradation in terms of data loss,

throughput, and latency. Rapid turnaround time

from transmit to receive and speedy wakeup from

sleep mode can add significance to power savings

[8].

Energy efficient hardware is also an issue; existing

wireless technologies draw relatively high peak

current and mainly rely on duty cycling the radio

between sleep and active modes to minimize the

average current drawn. Researchers are exploring

several promising techniques such as low-power

listening and wake-up radios, which are intended to

minimize power consumed by idle listening.

BANs are meant to support medical applications

mainly. Hence, safety, security, QoS, and reliability

are important factors besides energy efficiency.

Coexistence of multiple BANs in crowded places

such as hospitals needs a robust MAC protocol.

Efficient duty cycling methods need to be

developed to minimize power consumption. The

MAC protocol should be able to cope with

topology changes caused by movement of nodes.

Channel migration protocols need to be developed

to be able to migrate to a quiet channel when

serious hindrance is noticed. A simple network


22

setup process is vital for the ease of amateur users

[8].

In [3], Omeni et al, have presented energy efficient

medium access protocol for wireless medical body

area sensor networks. Using single-hop

communication and centrally controlled

sleep/wakeup times leads to considerable energy

reductions for this application compared to more

flexible network MAC protocols such as 802.11 or

Zigbee. The general power utilization reaches the

standby power as duty cycle is reduced. The

protocol is implemented in hardware as part of the

Sensium™ system-on-chip WBASNASIC, in a

0.13- Mcmos process.

Privacy, confidentiality, authentication,

authorization, and integrity are fundamental

requirements. Traditional security and privacy

techniques are not appropriate for BANs due to

bounded processing power, memory, and energy,

lack of user interface, unskilled users, and global

roaming. Hence, novel lightweight and resource-

efficient methods have to be developed for BANs

[1]. Global roaming over heterogeneous

infrastructure networks further complicates the

end-to-end security provisions.

Medical devices are subject to strict regulations to

promote the safety and welfare of users.

Compliance to applicable regulations set forth by

the FCC, U.S. Food and Drug Administration

(FDA), European Telecommunications Standards

Institute (ETSI), and other regulatory agencies is

essential [1].

5. Candidate Wireless Technologies

In this section, various wireless technologies that

are leading competitors in the upcoming market of

BANs are discussed. End-to-end performance is

determined by the complete protocol stack (i.e.,

including PHY and upper protocol layers).

Bluetooth classic: Bluetooth is a short range

wireless communication standard that defines the

link and application layers to support data and

voice applications. Up to eight Bluetooth devices

form a shortrange network called a piconet.

Bluetooth SIG has developed the Bluetooth Health

Device Profile (HDP) that defines the requirements

for qualified Bluetooth healthcare and fitness

device implementations [1].

Bluetooth low energy: Bluetooth Low Energy

(BTLE) is an upcoming standard that provides

ultra-low-power idle mode operation, simple device

discovery, and reliable point-to-multipoint data

transfer with power save and encryption

functionalities. The key advantages of BTLE are

the strength of the Bluetooth brand and the promise

of interoperability with Bluetooth radios in mobile

phones [1].

ZigBee: ZigBee defines a network, security, and

application layer protocol suite on top of the PHY

and MAC layers defined by the IEEE 802.15.4

WPAN standard. The PHY exploits the direct

sequence spread spectrum technique for

interference tolerance and MAC exploits carrier

sense multiple access with collision avoidance

(CSMA/CA) for channel access. Zigbee provides

full support for IEEE 11073 devices including

glucometers, pulse oximeters, electro-cardiographs,

weight scales, thermometers, blood pressure

monitors, and respirometers[12].

ANT: ANT is a proprietary technology designed

for general-purpose wireless sensor network

applications. ANT features simple design, low

latency, the ability to trade off data rate against

power consumption, and a net data rate of 20 kb/s

(over-the-air data rate is 1 Mb/s)[12].

Sensium: Sensium is a proprietary ultra-low-

power transceiver platform custom designed for

healthcare and lifestyle management applications.

The network adopts a master-slave architecture,

joining a network is centrally managed, and all

communications are single- hop[12].

Zarlink: Zarlink has developed an ultra-low-

power RF transceiver, ZL70101, for medical

implantable applications. It uses a Reed- Solomon

coding scheme together with cyclic redundancy

check (CRC) error detection to achieve an

extremely reliable link. The key features of Zarlink

ZL70101 are extremely low power consumption,

ultralow- power wakeup circuit, and MedRadio

compliance [12].

Other technologies: Proprietary RF

technologies such as BodyLAN and Z-Wave are

also emerging on the horizon. Inductive coupling

(IC) and body coupled communications (BCC)

technologies are also promising. The data rate of IC

is limited, and it cannot initiate communication

from inside the body. BCC transceivers are

capacitively coupled to the skin and use the human

body as a channel to exchange data. BCC is energy

efficient, and alleviates interference and

coexistence issues. BCC can also be used for user

identification and automatic formation of BANs

[1].

6. Challenging Practical Issues


23

BANs face several important challenging issues,

most of which arise from efficiency and practicality

aspects. These issues constrain the solution space,

and need to be considered carefully when designing

mechanisms for data security and privacy in

WBANs.

Conflict between security and efficiency: High efficiency is strongly demanded for data

security in WBANs, not only because of the

resource constraints, but also for the applications.

Wearable sensors are often extremely small and

have insufficient power supplies, which render

them inferior in computation and storage

capabilities. Thus, the cryptographic primitives

used by the sensor nodes should be as lightweight

as possible, in terms of both fast computation and

low storage overhead.

Conflict between security and safety: Whether the data can be accessed whenever needed

could be a matter of patients’ safety. Too strict and

inflexible data access control may prevent the

medical information being accessed in time by

legitimate medical staff, especially in emergency

scenarios where the patient may be unconscious

and unable to respond. On the other hand, a loose

access control scheme opens back doors to

malicious attackers. It is hard to ensure strong data

security and privacy while allowing flexible access.

Conflict between security and usability:

The devices should be easy to use and foolproof,

since their operators might be non-expert patients.

As the setup and control process of the data

security mechanisms are patient-related, they shall

involve few and intuitive human interactions. For

instance, to bootstrap initial secure communication

between all the nodes in a WBAN for secure data

communication, device pairing techniques can be

adopted. Increasing usability by omitting some

manual steps may not be good for security.

Requirement for device

interoperability: Patients may buy sensor

nodes from different manufacturers, among which

it is difficult to pre-share any cryptographic

materials. It is difficult to establish data security

mechanisms that require the least common settings

and efforts, and work with a wide range of devices.

7. Positioning of WBAN User

Positioning of a WBAN user in critical condition is

an important issue in WBAN. A patient equipped

with WBAN sensors can get stuck into any

critical condition anywhere so it is important to

monitor them continuously. There are different

technologies for localization, but their stickiness

with certain application does not make them

unanimous. In WBAN a technology is needed

which can serve two way communication as well as

positioning of the user. Since GSM technology is

dispersed worldwide with huge infrastructure so

GSM is better option than others, because of the

two way communication and positioning we can

rely upon single entity [7].

8. Conclusion

The WBAN is an emerging and promising

technology that will change people’s healthcare and

daily life experiences revolutionarily. Data

security, safety, efficiency and privacy in WBANs

is an important area, and there still remain a

number of considerable challenges to overcome.

The research in this area is still in its infancy now,

but it is believed it will draw an enormous amount

of interest in coming years. This paper has

highlighted many research and practical issues

related to BANs. Addressing all these challenges is

most likely to require new approaches to media

access and protocol design. Engineers, researchers,

and practitioners from multiple disciplines, must

come together and strive hard to overcome

technical roadblocks in order to bring the vision of

a ubiquitous body area network to reality.

References

[1] Maulin Pateland Jianfeng Wang, ―Applications,

Challenges, And Prospectivein Emerging Body

Area Networking Technologies‖ IEEE Wireless

Communications, February 2010.

[2] Mark A. Hanson, Harry C. Powell Jr., Adam T.

Barth, Kyle Ringgenberg, Benton H. Calhoun,

James H. Aylor, John Lach, ―Body Area Sensor

Networks: Challenges And Opportunities‖, IEEE

Computer Society, January 2009.

[3] Okundu Omeni, Alan Chi Wai Wong, Alison J.

Burdett, Christofer Toumazou, ―Energy Eficient

Medium Access Protocol For Wireless Medical

Body Area Sensor Networks‖, IEEE Transactions

On Biomedical Circuits And Systems, Vol.2, No.4,

December 2008.

[4] George Koutitas, ―Multiple Human Effects In

Body Area Networks‖ IEEE Antennas And

Wireless Propagation Letters, Vol.9, 2010.

[5] Elisabetta Farella, Augusto Pieracci, Luca

Benini, Laura Rocchi, Andrea Acquaviva,

―Interfacing Human And Computer With Wireless

Body Area Sensor Networks: The Wimoca


24

Solution‖, Springer Science + Business Media,

January 2008.

[6] Conway, Simonl Cotton, Williamg Scanlon,

―An Antennas And Propagation Approach To

Improving Physical Layer Performance In Wireless

Body Area Networks‖ IEEE Journal On Selected

Areas In Communications, Vol.27, No.1,

January2009.

[7] Md. Asdaque Hussain, Kyung Sup Kwak,

―Positioning In Wireless Body Area Network

Using Gsm‖ International Journal Of Digital

Content Technology And Its Applications, Volume

3, Number 3, September 2009.

[8] Stefan Drude, ―Requirements And Application

Scenarios For Body Area Networks‖, Mobile And

Wireless Communications Summit, 2008.

[9] Ming Liand, Wenjing Lou, Kui Ren, ―Data

Security And Privacy In Wireless Body Area

Networks‖, IEEE Wireless Communications,

February 2010.

[10] Juan M. Corchado, Javierbajo, Dantei. Tapia,

Ajith Abraham, ―Using Heterogeneous Wireless

Sensor Networks In A Telemonitoring System For

Healthcare‖, IEEE Transactions On Information

Technology In Biomedicine, Vol.14, No.2, March

2010.

[11] Shuo Xiao, Ashay Dhamdhere,Vijay

Sivaraman,Alison Burdett, ―Transmission Power

Control In Body Area Sensor Networks For Health

Care Monitoring―, IEEE Journal On Selected Areas

In Communications, Vol.27, No.1, January2009.

[12] Huasong Cao, Victor Leung, Cupid Chow,

Henry Chan, ―Enabling Technologies For Wireless

Body Area Networks: A Survey And Outlook‖,

IEEE Communications Magazine, December 2009.

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