coordinated sensor deployment for improving secure communications and sensing coverage yinian mao,...

Coordinated Sensor Deployment for Improving Secure Communications and Sensing CoverageYinian Mao, Min WuSecurity of ad hoc and Sensor Networks,Proceedings of the 3rd ACM workshop on Security of ad hoc and sensor networks, November 07 - 07, 2005

Paper Review

Jun Sup LeeDependable Software LAB at KAISTNov. 21th 2006

Agenda

Introduction

Problem Statement

Contribution

Contents

Background

Static Sensor deployment

Location Adjustment

Conclusion

Q&A

Introduction| Sensor Network and Security

Sensor Network – Great Potential in application

Habitat monitoring

Wildlife tracking

Building surveillance

Military combat

Important design Issue

Efficient sensing coverage

Node-to-node or node-to-base-station communications

Security in information gathering and relay by the sensors

This paper shows that the system performance on these aspects

How the sensors are deployed in the field

How the sensor locations can be adjusted after the initial deployment

Introduction | Sensor Network and Security | characteristic

Sensing and Communication on Sensor Node Limitation of sensing range and the communication range

because of physical characteristics

Placement of sensor nodes will have great impacts on sensing coverage

communication connectivity

Rely on Wireless Transmission malicious adversaries could intercept the communications

Modify the data packets, or inject falsified packets.

Message authentication code with cryptographic

Symmetric key cryptography lower computational complexity

Preferred in practice

Key Pre-distribution

Introduction | Contribution

Analyze Impact on secure connectivity and sensing coverage

Static Sensor deployment

Hexagon lattice topology

Square lattice topology

Location adjustment after deployment

VFSec algorithm

Weighted Centroid algorithm

A new framework for coordinated updates of sensor locations.

Jointly optimize sensing coverage and secure connectivity

Current Work

Optimize the sensing coverage

Do not concern secure sensor communication

Background | Sensing Coverage and Sensing Capability

Sensing Coverage

Rs : Sensing radius

d(*,*) : Euclidean distance

S = 1 : sensor has the capability to sense

S = 0 : otherwise

Sensing Capability

Rc : Communication radius

d(*,*) : Euclidean distance

T = 1 : link exists

T = 0 : otherwise

Background | Efficient Sensing in Static Deployment

Static Deployment

Sensing efficiency ratio – (Circle covering problem : covering density, covering thickness)

, ,

Acol : actual covered area by all the sensor nodes

Aseq : sum of the area covered by each individual sensor

Lowerbound : (by hexagon lattice)

Nomalize distance D1

D1 : distance to its horizontal/vertical neighbor in Square lattice deployment

D2 : distance to its diagonal neighbor in Square lattice deployment

D3 : distance from a node to its six neighbors in hexagon lattice deployment

Background | Key Pre-distribution for Sensor Networks

Key pre-distribution in WSNs

Loading Keys into sensor nodes prior to deployment

Two nodes find a common key between them after deployment

Challenges

Memory/Energy efficiency

Security: nodes can be compromised

Scalability: new nodes might be added later

Each noderandomly selects R keys (Key Ring)

N1N2 …

Key Pool P

N4N3• When |P| = 1000, R=20 / 30

p (two nodes have a common key) = 0.335 / 0.605

Lattice-Structured Deployment | Fundamental Relations Between Deployment Lattices

Expected number of secure links versus communication radius

Square lattice and Hexagon lattice, key-pre distribution

: Key sharing probability

Lattice-Structured Deployment | Secure Connectivity Under Perturbed Deployment Lattice

Expected number of secure links per node versus communication radius.

Actual deployment location :

r : zero-mean distribution with Gaussian

Probability that a designed neighbor in the hexagon lattice can establish a secure link with the center node :

expected number of secure links for the center node (hexagon):

expected number of secure links for the center node (square):

A : horizontal/vertical neighbors

B : diagonal neighbors

Lattice-Structured Deployment | Secure Connectivity Under Perturbed Deployment Lattice

Expected number of secure links per node versus communication radius.

Key ring 100 / Key pool : 1200

Location Adjustment : Virtual Force | Effect on Secure Connectivity by the Existing Approach

Virtual Force algorithm

Maximize total sensing coverage

: Unit-length pointing from the location of ni to nj.

Move Node ni

Direction :

Magnitude :

Location Adjustment : Virtual Force | Effect on Secure Connectivity by the Existing Approach

Impact of location adjustment to the establishment of secure links using VFA

Half of the nodes are no longer connected with the largest connected group, which reduces the capability of secure communications between the sensor nodes.

Location Adjustment : VFSec | VFSec

VFSec Algorithm

Performance metric : ( : total sensing coverage, : secure link per node)

While average number of secure links per node is around 3

W1 = 1

W2 = 1/3

VFSec

Location Adjustment : VFSec | Simulation Results

Comparison of VFA and VFSec with Uniform random initial deployment

Location Adjustment : VFSec | Simulation Results

Comparison of VFA and VFSec using square deployment lattice under Gaussian deployment deviation.

Comparison of deployment lattice using VFSec under Gaussian deployment deviation.

Location Adjustment : WTC | Weighted Centroid Algorithm

Weighted Centroid Algorithm

1. Compute Voronoi cell V

2. Generate uniform grid points

3. Assign weight using assignment procedure

4. Compute location :

5. Compute the movement vector

Location Adjustment : WTC | Simulation Results

Comparison of the WTC and minmax algorithm, small Gaussian deployment deviation, hexagon lattice - key pre-distribution.

Comparison of the WTC and minmax algorithm, large Gaussian deployment deviation, hexagon lattice - key pre-distribution.

Location Adjustment : WTC | Simulation Results

Comparison of the weighted centroid and minmax algorithm, uniform random deployment with basic key pre-distribution.

Conclusion| Conclusions and outlook of this paper

Static sensor deployment

Square / Hexagon lattice

two lattice topology exhibits range-dependent performance

there is no all-time winner in the context of secure connectivity

Location Adjustment

VFSec / WTC

WTC algorithm outperforms under moderate to abundant node density

VFSec algorithm outperforms than the existing virtual force based algorithms

WTC is more suitable to be performed by individual sensors than VF

Performing WTC generally requires more computation than performing schemes based on virtual force

Thank you

Question?

For more discussion:

Rm4428, Jslee@dependable.kaist.ac.kr