Jamming and Eavesdropping Defense in Green Cyber–Physical Transportation Systems Using a Stackelberg Game

This paper studies the secure transmission rate issue between sensors and the remote controller to defend the jamming and eavesdropping attacks in green cyber–physical transportation systems. In this system, the traffic sensor transmits the transportation state information to the remote controller via wireless networks. Due to the broadcast characteristics of the wireless communication, the systems are vulnerable to the eavesdropping and jamming attacks. In this paper, we study how to maximize the secure transmission rate between sensors and the controller in the presence of a malicious eavesdropper and a jammer. Specifically, the malicious jammer is smart and can choose the optimal power strategy to maximize the side effect with the knowledge of sensor's transmission power. For the purpose of achieving the maximum utility, the optimal strategy is determined via adjusting the sensor's transmission power according to the control feedback conditions. We consider the single-antenna model and the multiantenna model to formulate this problem as an optimization problem based on a Stackelberg game. We then prove the existence of the Stackelberg equilibrium via the interaction between the sensor and the jammer. Moreover, we present two algorithms to obtain the optimal transmission strategy, i.e., a stochastic algorithm with feedback and renewed intelligent simulated annealing. Finally, extensive simulations and trace experimental results are presented to verify our theoretical analysis.

[1]  Quanyan Zhu,et al.  A moving-horizon hybrid stochastic game for secure control of cyber-physical systems , 2014, 53rd IEEE Conference on Decision and Control.

[2]  Yan Zhang,et al.  Enabling Localized Peer-to-Peer Electricity Trading Among Plug-in Hybrid Electric Vehicles Using Consortium Blockchains , 2017, IEEE Transactions on Industrial Informatics.

[3]  Song Guo,et al.  Green Resource Allocation Based on Deep Reinforcement Learning in Content-Centric IoT , 2018, IEEE Transactions on Emerging Topics in Computing.

[4]  Rong Yu,et al.  Exploring Mobile Edge Computing for 5G-Enabled Software Defined Vehicular Networks , 2017, IEEE Wireless Communications.

[5]  Zhu Han,et al.  Physical layer security game: How to date a girl with her boyfriend on the same table , 2009, 2009 International Conference on Game Theory for Networks.

[6]  Björn E. Ottersten,et al.  Improving Physical Layer Secrecy Using Full-Duplex Jamming Receivers , 2013, IEEE Transactions on Signal Processing.

[7]  S. Shankar Sastry,et al.  Secure Control: Towards Survivable Cyber-Physical Systems , 2008, 2008 The 28th International Conference on Distributed Computing Systems Workshops.

[8]  A. D. Wyner,et al.  The wire-tap channel , 1975, The Bell System Technical Journal.

[9]  Xi Fang,et al.  Coping with a Smart Jammer in Wireless Networks: A Stackelberg Game Approach , 2013, IEEE Transactions on Wireless Communications.

[10]  Robert Gibbons,et al.  A primer in game theory , 1992 .

[11]  Huiming Wang,et al.  Distributed Beamforming for Physical-Layer Security of Two-Way Relay Networks , 2012, IEEE Transactions on Signal Processing.

[12]  Aniruddha S. Gokhale,et al.  A Cyber Physical Systems Perspective on the Real-time and Reliable Dissemination of Information in Intelligent Transportation Systems , 2010, Netw. Protoc. Algorithms.

[13]  Toshiaki Miyazaki,et al.  Antieavesdropping With Selfish Jamming in Wireless Networks: A Bertrand Game Approach , 2017, IEEE Transactions on Vehicular Technology.

[14]  David Wetherall,et al.  Tool release: gathering 802.11n traces with channel state information , 2011, CCRV.

[15]  Jian Sun,et al.  Optimal data integrity attack on actuators in Cyber-Physical Systems , 2016, 2016 American Control Conference (ACC).

[16]  Min Gao,et al.  Probabilistic Model Checking and Scheduling Implementation of an Energy Router System in Energy Internet for Green Cities , 2018, IEEE Transactions on Industrial Informatics.

[17]  Yueming Cai,et al.  Cooperative jammer power allocation — A Nash bargaining solution method , 2015, 2015 International Conference on Wireless Communications & Signal Processing (WCSP).

[18]  Claude E. Shannon,et al.  Communication theory of secrecy systems , 1949, Bell Syst. Tech. J..

[19]  Yafeng Yin,et al.  Privacy-Preserving Transportation Traffic Measurement in Intelligent Cyber-physical Road Systems , 2016, IEEE Transactions on Vehicular Technology.

[20]  Rodrigo C. de Lamare,et al.  Joint iterative power allocation and relay selection for cooperative MIMO systems using discrete stochastic algorithms , 2011, 2011 8th International Symposium on Wireless Communication Systems.

[21]  Zhu Han,et al.  Improve physical layer security in cooperative wireless network using distributed auction games , 2011, 2011 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS).

[22]  Jie Xu,et al.  Proactive Eavesdropping via Cognitive Jamming in Fading Channels , 2015, IEEE Transactions on Wireless Communications.

[23]  Chase Qishi Wu,et al.  A Survey of Game Theory as Applied to Network Security , 2010, 2010 43rd Hawaii International Conference on System Sciences.

[24]  Zhu Han,et al.  Game theoretic modeling of jamming attack in wireless powered communication networks , 2015, 2015 IEEE International Conference on Communications (ICC).

[25]  Song Guo,et al.  Green Industrial Internet of Things Architecture: An Energy-Efficient Perspective , 2016, IEEE Communications Standards.

[26]  Seong-Lyun Kim,et al.  Random power control in wireless ad hoc networks , 2005, IEEE Communications Letters.

[27]  Yanfei Sun,et al.  Strategic Honeypot Game Model for Distributed Denial of Service Attacks in the Smart Grid , 2017, IEEE Transactions on Smart Grid.

[28]  Song Guo,et al.  Strategic Antieavesdropping Game for Physical Layer Security in Wireless Cooperative Networks , 2017, IEEE Transactions on Vehicular Technology.

[29]  Jian Shen,et al.  Game-Theory-Based Active Defense for Intrusion Detection in Cyber-Physical Embedded Systems , 2016, ACM Trans. Embed. Comput. Syst..

[30]  Shengli Xie,et al.  Fair Energy Scheduling for Vehicle-to-Grid Networks Using Adaptive Dynamic Programming , 2016, IEEE Transactions on Neural Networks and Learning Systems.

[31]  M. Guirguis,et al.  A Case for Low-level Jamming Attacks on Mobile CPS in Target Tracking Applications , 2012, 2012 12th International Symposium on Pervasive Systems, Algorithms and Networks.

[32]  Chao Yang,et al.  Topology-Aware Vehicle-to-Grid Energy Trading for Active Distribution Systems , 2019, IEEE Transactions on Smart Grid.

[33]  Dietmar P. F. Möller,et al.  Cyber-physical systems in smart transportation , 2016, 2016 IEEE International Conference on Electro Information Technology (EIT).

[34]  Hongning Dai,et al.  Friendly-Jamming: An anti-eavesdropping scheme in wireless networks , 2017, 2017 IEEE 18th International Symposium on A World of Wireless, Mobile and Multimedia Networks (WoWMoM).