Mitigating Selective Jamming Attacks in Smart Meter Data Collection using Moving Target Defense

In Advanced Metering Infrastructure (AMI) networks, power data collections from smart meters are static. Due to such static nature, attackers may predict the transmission behavior of the smart meters which can be used to launch selective jamming attacks that can block the transmissions. To avoid such attack scenarios and increase the resilience of the AMI networks, in this paper, we propose dynamic data reporting schedules for smart meters based on the idea of moving target defense (MTD) paradigm. The idea behind MTD-based schedules is to randomize the transmission times so that the attackers will not be able to guess these schedules. Specifically, we assign a time slot for each smart meter and in each round we shuffle the slots with Fisher-Yates shuffle algorithm that has been shown to provide secure randomness. We also take into account the periodicity of the data transmissions that may be needed by the utility company. With the proposed approach, a smart meter is guaranteed to send its data at a different time slot in each round. We implemented the proposed approach in ns-3 using IEEE 802.11s wireless mesh standard as the communication infrastructure. Simulation results showed that our protocol can secure the network from the selective jamming attacks without sacrificing performance by providing similar or even better performance for collection time, packet delivery ratio and end-to-end delay compared to previously proposed protocols.

[1]  Gianluca Dini,et al.  SAD-SJ: A self-adaptive decentralized solution against Selective Jamming attack in Wireless Sensor Networks , 2013, 2013 IEEE 18th Conference on Emerging Technologies & Factory Automation (ETFA).

[2]  Kemal Akkaya,et al.  Investigation of Smart Meter Data Reporting Strategies for Optimized Performance in Smart Grid AMI Networks , 2017, IEEE Internet of Things Journal.

[3]  Ehab Al-Shaer,et al.  Randomizing AMI configuration for proactive defense in smart grid , 2013, 2013 IEEE International Conference on Smart Grid Communications (SmartGridComm).

[4]  Kirill V. Andreev,et al.  Simulation Study of VoIP Performance in IEEE 802.11 Wireless Mesh Networks , 2010, MACOM.

[5]  R. A. Fisher,et al.  Statistical Tables for Biological, Agricultural and Medical Research , 1956 .

[6]  Taskin Koçak,et al.  Smart Grid Technologies: Communication Technologies and Standards , 2011, IEEE Transactions on Industrial Informatics.

[7]  Yang Xiao,et al.  A survey of communication/networking in Smart Grids , 2012, Future Gener. Comput. Syst..

[8]  Ian F. Akyildiz,et al.  A survey on wireless sensor networks for smart grid , 2015, Comput. Commun..

[9]  Ismail Güvenç,et al.  Secure Data Obfuscation Scheme to Enable Privacy-Preserving State Estimation in Smart Grid AMI Networks , 2016, IEEE Internet of Things Journal.

[10]  Kemal Akkaya,et al.  Periodic data reporting strategies for IEEE 802.11s-based Smart Grid AMI networks , 2014, 2014 IEEE International Conference on Smart Grid Communications (SmartGridComm).

[11]  Manuel Blum,et al.  A Simple Unpredictable Pseudo-Random Number Generator , 1986, SIAM J. Comput..

[12]  Kemal Akkaya,et al.  A survey of routing protocols for smart grid communications , 2012, Comput. Networks.

[13]  Minghui Zhu,et al.  Comparing Different Moving Target Defense Techniques , 2014, MTD '14.

[14]  Saifur Rahman,et al.  Communication network requirements for major smart grid applications in HAN, NAN and WAN , 2014, Comput. Networks.

[15]  Scott A. DeLoach,et al.  Investigating the application of moving target defenses to network security , 2013, 2013 6th International Symposium on Resilient Control Systems (ISRCS).

[16]  Kirill Andreev,et al.  IEEE 802 . 11 s Mesh Networking NS-3 Model , 2010 .

[17]  Richard Moulds,et al.  Quantum Random Number Generators , 2016 .

[18]  Young-Bae Ko,et al.  Improving the reliability of IEEE 802.11s based wireless mesh networks for smart grid systems , 2012, Journal of Communications and Networks.

[19]  Younghwan Yoo,et al.  Design and Implementation of MAC Protocol for SmartGrid HAN Environment , 2011, 2011 IEEE 11th International Conference on Computer and Information Technology.

[20]  J. Wishart Statistical tables , 2018, Global Education Monitoring Report.

[21]  Loukas Lazos,et al.  Selective Jamming Attacks in Wireless Networks , 2010, 2010 IEEE International Conference on Communications.

[22]  Jack W. Davidson,et al.  Moving Target Defenses in the Helix Self-Regenerative Architecture , 2013, Moving Target Defense.

[23]  Ronald L. Rivest,et al.  Introduction to Algorithms, Second Edition , 2001 .

[24]  Christian Wietfeld,et al.  Multimedia over 802.15.4 and ZigBee Networks for Ambient Environment Control , 2007, 2007 IEEE 65th Vehicular Technology Conference - VTC2007-Spring.

[25]  Wenyuan Xu,et al.  The feasibility of launching and detecting jamming attacks in wireless networks , 2005, MobiHoc '05.

[26]  Miroslaw Malek,et al.  NPART - node placement algorithm for realistic topologies in wireless multihop network simulation , 2009, SimuTools.

[27]  Vijay V. Vazirani,et al.  Efficient and Secure Pseudo-Random Number Generation (Extended Abstract) , 1984, FOCS.