Yi Qian

Department of Electrical and Computer EngineeringUniversity of Nebraska, NE, USA

E-mail: yi.qian@unl.edu

Web: cns.unl.edu/yqian

October 18, 2016

Recent Research in Smart Recent Research in Smart Recent Research in Smart Recent Research in Smart Grid Communication Grid Communication Grid Communication Grid Communication

Infrastructures and Cyber SecurityInfrastructures and Cyber SecurityInfrastructures and Cyber SecurityInfrastructures and Cyber Security

Introduction to Smart Grid

2

SMARTGRID

UPGADE

CO

NT

RO

LDEMANDRESPONSE

GENERATORRENEWABLE

SO

UR

CE

S

EFF

ICIE

NC

YPEAK

LOAD

AD

VA

NC

ED

COMMUNICATIONS

WIRELESSTRANSMISSION

RELIABILITYENHANCED

EVOLUTION

ELECTRICITY

SY

ST

EM

DE

VIC

ES

INFORMATION

NETWORK

TECHNOLOGIES

BIG

DA

TA

CLOUD

COMPUTING

MET

ER

SMOOTH

CONSUMERSERVICE

TWO-WAY

Motivations & Objectives of Smart Grid

3

• Higher Penetration

of Renewables

• Smart Charging of

Electric Vehicles

• Consumers to

Control Energy Bills

• Efficient Grid

Operations &

Reduced Losses

• Reduced

Distribution

Outages

• Improved System

Reliability &

Security

Lower Greenhouse Gas Emission

Facilitated renewable resource generation

Increased productivity

Improved utilization

Enhanced customer experience

Adherence to regulatory constraints

What is Smart Grid?

• An upgrade on upgrading generation, transmission, and distribution systems

• Incorporating advanced information and communications technologies (ICT) and control

• DoE defines Smart Grid in terms of key functions

‒ Enabling active participation by consumers to adjust consumption based on price and overall demand

‒ Better matching generation and demand

‒ Integrating renewable (e.g., solar, hydro, wind, etc.) and distributed power generation sources

‒ Providing more and better energy storage options

‒ Improving power quality, reliability, and enhancing resiliency: wide area situational awareness (WASA)

4

Demand

response

The ICT Framework in Smart Grid

5

Proposed ICT Framework

6

(Big) Data

Analytics

USEFUL INFO

RAW DATA

Information and Communication

Technologies (ICT)

Two-way communications

Networks in the ICT Framework

• Private networks: deployed by utility companies• Networks in the advanced metering infrastructure (AMI)

• Metering data gathering

• Demand response control message distribution

• Networks in the wide area monitoring systems (WAMS)• Monitoring data gathering

• Controlling message distribution

• Etc.

• Public networks: Internet based public network service• Remote monitoring and control from smart phones

• E.g., smart appliances that have Wi-Fi connection to the Internet

• Data transmission through cellular network service • E.g., transactional data from EVs

• Applying public cloud computing service• For big data analytics

• Etc.

7

Advanced Metering Infrastructure (AMI)

8

Backbone

(Fiber optics)

Advanced metering infrastructure

(AMI) enables two-way

communication between utilities

and customers.

MDMS (Metering

Data Management

System)

9Source: http://sine.ni.com/cs/app/doc/p/id/cs-16856#prettyPhoto

Smart Appliances

10

Figure sources: http://insidebitcoins.com/news/bitcoin-and-the-economy-of-things/26486

http://news.filehippo.com/2013/03/smart-grid-the-future-of-home-appliances/

http://housesogreen.com/2012/08/review-lennox-icomfort-wi-fi-thermostat-sonos-for-air-conditioners/

http://www.isustainableearth.com/green-products/the-lowdown-on-modern-electric-vehicles

http://www.engadget.com/2015/02/03/irl-a-month-controlling-my-coffeemaker-over-wifi/

Security in the ICT Framework

11

Security Requirements

• Various types of data in smart grid communications have different security requirements as well as delay requirements

12

Confidentiality Integrity Non-repudiation

Demand

Response

Pricing forecast X X

Energy forecast X X X

Metering data X X X

Wide Area

Monitoring System

Monitoring data X

Control message X X

Cloud ComputingPre-processed data X X X

Raw energy forecast X X X

External Sources Other information X

Security Mechanisms

• Authentication and key management process for private networks.

• Illustrated with DAPs in AMI as communication nodes13

Uninitialized Active neighbor AS�1 �2

�1 = request�|��1|��1||����1 + �1 + �1�

�2 = ��2||��2��1||��2||�2�||����2 + �2 + �2�

�′3 = ��1 ���1�|�1|��3�|��� |�!"||����2 +∗�

�3 = ��2��′ ′

3�||���3′′ �

�4 = �′3�|��2|��5||����2 + �5�

�5 = ���2∗ ���1�||�6||����1 + �6�

�′′3 = �′3||�4||���′3 + �4�

�6 = �1,2

Active DAP

AS

�2

�3

�4

�1 DAP Active DAP

Active DAP

Initial authentication process• A supplicant sends request to all of its active

neighboring nodes

• The active neighboring nodes relay the

request to the AS Detailed process

Security Mechanisms (cont’d)

• Security schemes in uplink and downlink transmissions

14

Security scheme for uplink transmission (single link).

Security scheme for uplink transmission (multi

link aggregation).

XOR

()

H*�*�

E* �)||

tAuthentication

Server

t

Security scheme for downlink transmission.

XOR

(+

H*�*�

E* �+||

tAuthentication

Server

t�+

E

Broadcasting messages Individual messages

Security Mechanisms (cont’d)

15

Security scheme based on zero-knowledge proof for the proposed

distributed learning technique.

Security Mechanisms

• For internal data transmission over the Internet

• Utility company does not have complete control

‒ Huge amount of sensitive data goes through uncontrollable networks (by power companies)

• How to protect such transmission?

‒ We proposed to use identity-based security schemes to assist existing security schemes in the Internet and cloud computing servers

‒ More efficient security parameter management

‒ More control on the side of utility company

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• Anyone in the domain can generate public keys of other parties

• Public keys are refreshed easily

Private Key Generation

Expiration timeIdentity

Public Key Generation

• Private keys are generated by private key

generator (PKG)

• Outdated private keys are easily revoked

Proposed ID-Based Signcryption

17

Preliminaries

Bilinear mapping:

• Bilinearity: for all and .

• Non-degeneracy: for any for all .

• Computability: there is a polynomial time algorithm for computing for all .

Proposed ID-based signcryption scheme

Controlled by utility companies

Analysis of the IBSC Scheme

18

Modified Weil pairing is adopted to

apply performance analysis Weil pairing

over supersingular elliptic curve

Modified Weil pairing: ,

where and is a

primitive cube root of unity in .

Security analysis

The security of the proposed IBSC is based on the following computational problems

•Computational Diffie-Hellman Problem: given �, ,�, -�, .� ∈ 01, ∀,, -, . ∈ 34∗ , there is no

polynomial time algorithm to compute ,-� ∈ 01•Bilinear Diffie-Hellman Problem: given �, ,�, -�, .� ∈ 01, ∀,, -, . ∈ 34

∗ , there is no polynomial

time algorithm to compute 5̂ �, � 789 ∈ 0:

Performance analysis

# of

;<# of

mul

# of

=>

# of

=?

# of

=@

Signcrypt 1 5 1 2 1

Decrypt 1 0 0 0 1

Sign 0 3 1 0 0

Verify 3 1 1 1 0

A = ?BC -DE = ?BC -

A = ?BC -DE = B>? -

A = @FB -DE = ?BC -

A = @FB -DE = B>? -

Signcrypt 39.59 ms 68.89 ms 45.4 ms 74.7 ms

Decrypt 7.44 ms 7.44 ms 13.25 ms 13.25 ms

Sign 19.29 ms 36.87 ms 19.29 ms 36.87 ms

Verify 28.75 ms 34.61 ms 46.18 ms 52.04 ms

G ≡ 2 IJK 3G = ,L − 1, for some prime Gand positive integer ,�N is the multiplier in 01

Intel Core

i5 @ 3.1

GHz & 8G

RAM

Possible Applications of the Proposed IBSC Scheme

• Short message encipherment

• Digital signature

• Session key distribution

• Signing right delegation

19One to one

One to many

Signing right delegation• When a local control center is under maintenance

• Not available due to cyber attack/natural disaster

• Etc.

Future Research Directions

20

Future Research Directions

• Optimization of renewable power source deployment and operation

• To better accommodate the management of fossil fuel based power sources

• Fast and reliable learning techniques for big data analytics

• Power consumption analysis

• Smart pricing analysis

• Real time anomaly detection (e.g., PMU data)

• Large scale graph modeling techniques

• To better analyze the relationship among pieces of information

• Parallel computing and cloud computing

• To speed up computation

• To enhance scalability

21

Future Research Directions (cont’d)

• Better integration of EVs

• Fast vehicular network for data exchange

• (Near) real-time big data analytics for EVs

• Cyber security

• Fast privacy protection

• without traditional encryption algorithms

• Or fast encryption algorithms

• Real-time data integrity protection

• Real-time anomaly detection, etc.

• Cloud security

• Etc.

22

Conclusion

23

Conclusion

• Smart grid is a massive cyber physical system

• Advanced ICT are applied in smart grid communication infrastructures

• Smart grid generates big data

• Big data analytics is important to DR, monitoring system, and other applications in smart grid

• Many issues remain open in big data research of smart grid communications

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AcknowledgementThis work was supported by the National Science Foundation under the grant CNS-1423408

References[1]. F. Ye, Y. Qian and R. Q. Hu, “Identity-Based Schemes for a Secured Big Data and Cloud ICT

Framework in Smart Grid”, to appear Security and Communication Networks.

[2]. J. Jiang and Y. Qian, “Distributed Communication Architecture for Smart Grid Applications”, to appear IEEE Communications.

[3]. X. Long, D. Tipper, Y. Qian, “A Key Management Architecture for Secure Smart Grid Communications”, to appear Security and Communications Networks.

[4]. S. Ma, Y. Yang, Y. Qian, Hamid Sharif, and Mahmoud Alahmad, “Energy Harvesting for Wireless Sensor Networks: Applications and Challenges in Smart Grid”, International Journal of Sensor Networks, Vol.21, No.4, pp.226-241, 2016.

[5]. F. Ye, Y. Liang, H. Zhang, X. Zhang, and Y. Qian, “Design and Analysis of a Wireless Sensor Based Monitoring Network for Transmission Lines in Smart Grid”, Wireless Communications and Mobile Computing, Vol.16, No.10, pp.1209-1220, July 2016.

[6]. F. Ye, Y. Qian and R. Q. Hu, “A Real-time Information Based Demand-Side Management System in Smart Grid”, IEEE Transactions on Parallel and Distributed Systems, Vol.27, No.2, pp.329-339, February 2016.

[7]. X. Zhang, F. Ye, S. Fan, J. Guo, G. Xu, and Y. Qian, “An Adaptive Security Protocol for a Wireless Sensor based Monitoring Network in Smart Grid Transmission Lines”, Security and Communication Networks, Vol.9, No.1, pp.60-71, January 2016.

[8]. S. Xu, Y. Qian and R. Q. Hu, “On Reliability of Smart Grid Neighborhood Area Networks”, IEEE

Access, Vol.3, pp.2352-2365, December 2015.

[9]. F. Ye, Y. Qian, R. Q. Hu, “HIBaSS: Hierarchical Identity-Based Signature Scheme for AMI Downlink Transmission”, Security and Communication Networks, Vol.8, No.16, pp.2901-2908, November 2015.

[10]. F. Ye and Y. Qian, “Secure Communication Networks in the Advanced Metering Infrastructure of Smart Grid”, ZTE Communications, Vol.13, No.3, pp.13-20, September 2015.

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[11]. F. Ye, Y. Qian, R. Q. Hu, and S. K. Das, “Reliable Energy-Efficient Uplink Transmission for Neighborhood Area Network in Smart Grid”, IEEE Transactions on Smart Grid, Vol.6, No.5, pp.2179-2188, September 2015.

[12]. F. Ye and Y. Qian, “Big Data and Cloud Computing Based Demand-Side Management for Electric Vehicles in Smart Grid”, IEEE COMSOC MMTC E-Letter, Vol.10, No.3, pp.28-30, May 2015.

[13]. F. Ye, Y. Qian, and R. Q. Hu, “Energy Efficient Self-Sustaining Wireless Neighborhood Area Network Design for Smart Grid”, IEEE Transactions on Smart Grid, No.1, pp.220-229, January 2015.

[14]. H. Wang, Y. Qian, and Hamid Sharif, “Multimedia Communications over Cognitive Radio Networks for Smart Grid”, IEEE Wireless Communications, Vol.20, No.4, pp.125-132, August 2013.

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[16]. J. Huang, H. Wang, Y. Qian, C. Wang, “Priority-based Traffic Scheduling and Utility Optimization for Cognitive Radio Communication Infrastructure-based Smart Grid”, IEEE Transactions on Smart

Grid, Vol.4, No.1, pp.78-86, March 2013.

[17]. Y. Yan, Y. Qian, H. Sharif, and D. Tipper, “A Survey on Smart Grid Communication Infrastructures: Motivations, Requirements and Challenges”, IEEE Communications Surveys and Tutorials, Vol.15, Issue 1, pp.5-20, 1st Quarter 2013.

[18]. Y. Yan, Y. Qian, H. Sharif, and D. Tipper, “A Survey on Cyber Security for Smart Grid Communications”, IEEE Communications Surveys and Tutorials, Vol.14, Issue 4, pp.998–1010, 4th Quarter 2012.

[19]. J. Zhou, R. Q. Hu and Y. Qian, “Scalable Distributed Communication Architectures to Support Advanced Metering Infrastructure in Smart Grid”, IEEE Transactions on Parallel and Distributed

Systems, Vol.23, No.9, pp.1632-1642, September 2012.

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[20]. S. Xu, Y. Qian and R. Q. Hu, “A Secure Data Learning Scheme in Big Data Applications”, Proceedings of The 25rd International Conference on Computer Communications and Networks (ICCCN 2016), August 1-4, 2016, Waikoloa, Hawaii, USA.

[21]. F. Ye, Y. Qian, R. Q. Hu, “A Big Data Driven and Cloud Computing Based ICT Framework for Smart Grid”, Proceedings of ICCCRI/CloudAsia 2016, Singapore, May 4-5, 2016. (Position Paper)

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[23]. S. Xu and Y. Qian, “Quantitative Study of Reliable Communication Infrastructure in Smart Grid NAN”, Poster Presentation, Proceedings of DRCN 2015, Kansas City, MS, March 25-27, 2015. (DRCN 2015 Best Poster Award)

[24]. F. Ye, Y. Qian and R. Q. Hu, “Design for Reliable and Self-Sustaining Neighborhood Area Network in Smart Grid”, Proceedings of DRCN 2015, Kansas City, MS, March 25-27, 2015.

[25]. F. Ye, Y. Qian, R. Q. Hu, “Self-Sustaining Wireless Neighborhood Area Network Design for Smart Grid”, Proceedings of IEEE Globecom 2014, Austin, Texas, December 8-12, 2014.

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[27]. Z. Guo, F. Ye, J. Guo, Y. Liang, G. Xu, X. Zhang, and Y. Qian, “A Wireless Sensor Network for Monitoring Smart Grid Transmission Lines”, Proceedings of The 23rd International Conference on Computer Communications and Networks (ICCCN 2014), Shanghai, China, August 4-7, 2014.

[28]. S. Fan, F. Ye, J. Guo, Y. Liang, G. Xu, X. Zhang, and Y. Qian, “A Security Protocol for Wireless Sensor Networks Designed for Monitoring Smart Grid Transmission Lines”, Proceedings of The 23rd International Conference on Computer Communications and Networks (ICCCN 2014), Shanghai, China, August 4-7, 2014.

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[29]. X. Long, D. Tipper, Y. Qian, “An Advanced Key Management Scheme for Secure Smart Grid Communications”, Proceedings of IEEE SmartGridComm’2013, Vancouver, Canada, October 21-24, 2013.

[30]. S. Bu, F. R. Yu and Y. Qian, “Energy-Efficient Cognitive Heterogeneous Networks Powered by the Smart Grid”, Proceedings of IEEE INFOCOM’2013, Turin, Italy, April 14-19, 2013.

[31]. J. Zhou, R. Q. Hu and Y. Qian, “Traffic Scheduling for Smart Grid in Rural Areas with Cognitive Radios”, Proceedings of IEEE Globecom’2012, Anaheim, CA, USA, December 3-7, 2012.

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[33]. J. Zhou, R. Q. Hu, X. Zhang and Y. Qian, “Price and Output Control in a Community Power Network with Renewable Generations”, Proceedings of IEEE SmartGridComm 2012, Tainan City, Taiwan, November 5-8, 2012.

[34]. J. Kamto, L. Qian, J. Fuller, J. Attia, Y. Qian, “Key Distribution and Management for Power Aggregation and Accountability in Advance Metering Infrastructure”, Proceedings of IEEE SmartGridComm 2012, Tainan City, Taiwan, November 5-8, 2012.

[35]. Y. Yan, Y. Qian and R. Q. Hu, “A Secure and Efficient Scheme for Machine-to-Machine Communications in Smart Grid”, Proceedings of IEEE ICC’2012, Ottawa, Canada, June 10-15, 2012.

[36]. R. Q. Hu, Y. Qian, H.H. Chen, A. Jamalipour, “Recent progress in machine-to-machine communications”, IEEE Communications Magazine, Vol.49, No.4, pp.24-26, April 2011

[37]. Y. Yan, Y. Qian, and Hamid Sharif, “A Secure Data Aggregation and Dispatch Scheme for Home Area Networks in Smart Grid”, Proceedings of IEEE Globecom’2011, Houston, Texas, December 5-9, 2011.

[38]. Y. Yan, Y. Qian, and Hamid Sharif, “A Secure and Reliable In-network Collaborative Communication Scheme for Advanced Metering Infrastructure in Smart Grid”, Proceedings of IEEE WCNC’2011, Cancun, Mexico, March 28-31, 2011.

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