Non-cooperative game of effective channel capacity and security strength in vehicular networks

Abstract Vehicular ad-hoc networks pose stringent requirements on quality-of-service (QoS) and security strength in parallel because of their open channels and highly dynamic topology. Harmonizing these two conflicting goals is an urgent challenge, especially in VNs that are characterized by restrictive resources, e.g. bandwidth and link lifetime. This paper aims to balance the anticipated QoS and security strength in context to fully utilize limited network and computing resources to attain a satisfactory performance rating without compromising any security. To this end, we use non-cooperative game theory to formulate node utility, synthesizing the channel capacity and security strength from the perspective of adaptively controlling the transmit power and encryption block length in Nakagami multipath fading (NMF) channels. Moreover, we analyze the non-cooperative behavior of a “communication player” in controlling the transmit power and a “security player” in deciding the encryption block length, both of whom together strive to maximize the utility function at minimum cost. We then theoretically derive the pure strategy Nash equilibrium. Extensive numerical calculations are conducted to comprehensively investigate the reaction of the Nash equilibrium against the various combinations of the considered parameters. The results show that the proposed joint optimization method is capable of self-adapting to the vehicular context and improving the communication quality without compromising on security.

[1]  Di Xiao,et al.  An efficient and noise resistive selective image encryption scheme for gray images based on chaotic maps and DNA complementary rules , 2014, Multimedia Tools and Applications.

[2]  Sanyang Liu,et al.  A Power Control Algorithm Based on Non-cooperative Game for Wireless Sensor Networks , 2011, 2011 International Conference on Computational and Information Sciences.

[3]  Li Zhao,et al.  LTE-V: A TD-LTE-Based V2X Solution for Future Vehicular Network , 2016, IEEE Internet of Things Journal.

[4]  Pravin Varaiya,et al.  Capacity of fading channels with channel side information , 1997, IEEE Trans. Inf. Theory.

[5]  Zhihua Xia,et al.  A Secure and Dynamic Multi-Keyword Ranked Search Scheme over Encrypted Cloud Data , 2016, IEEE Transactions on Parallel and Distributed Systems.

[6]  Xiaodong Lin,et al.  Complementing public key infrastructure to secure vehicular ad hoc networks [Security and Privacy in Emerging Wireless Networks] , 2010, IEEE Wireless Communications.

[7]  San-qi Li,et al.  A wireless channel capacity model for quality of service , 2007, IEEE Transactions on Wireless Communications.

[8]  M. Nakagami The m-Distribution—A General Formula of Intensity Distribution of Rapid Fading , 1960 .

[9]  Zhihua Xia,et al.  A Privacy-Preserving and Copy-Deterrence Content-Based Image Retrieval Scheme in Cloud Computing , 2016, IEEE Transactions on Information Forensics and Security.

[10]  Claude E. Shannon,et al.  The mathematical theory of communication , 1950 .

[11]  Mate Boban,et al.  Design aspects for 5G V2X physical layer , 2016, 2016 IEEE Conference on Standards for Communications and Networking (CSCN).

[12]  Yen-Cheng Chen,et al.  PAACP: A portable privacy-preserving authentication and access control protocol in vehicular ad hoc networks , 2011, Comput. Commun..

[13]  Kuei-Ping Shih,et al.  A Physical/Virtual Carrier-Sense-Based Power Control MAC Protocol for Collision Avoidance in Wireless Ad Hoc Networks , 2011, IEEE Transactions on Parallel and Distributed Systems.

[14]  Sungwook Kim Game Theory for Wireless Network Resource Management , 2018 .

[15]  Jeffrey G. Andrews,et al.  On the Throughput Cost of Physical Layer Security in Decentralized Wireless Networks , 2010, IEEE Transactions on Wireless Communications.

[16]  Weiwen Deng,et al.  VIKE: vehicular IKE for context-awareness , 2015, Wirel. Networks.

[17]  Yuguang Fang,et al.  An Identity-Based Security System for User Privacy in Vehicular Ad Hoc Networks , 2010, IEEE Transactions on Parallel and Distributed Systems.

[18]  J. Nash Equilibrium Points in N-Person Games. , 1950, Proceedings of the National Academy of Sciences of the United States of America.

[19]  Farzad Sabahi The Security of Vehicular Adhoc Networks , 2011, 2011 Third International Conference on Computational Intelligence, Communication Systems and Networks.

[20]  Mohammed Erritali,et al.  A beaconing approach whith key exchange in vehicular ad hoc networks , 2012, ArXiv.

[21]  Shamik Sengupta,et al.  A Game Theoretic Framework for Power Control in Wireless Sensor Networks , 2010, IEEE Transactions on Computers.

[22]  Neelakantan Pattathil Chandrasekharamenon,et al.  Connectivity analysis of one-dimensional vehicular ad hoc networks in fading channels , 2012, EURASIP Journal on Wireless Communications and Networking.

[23]  Rajarathnam Chandramouli,et al.  Opportunistic Encryption: A Trade-Off between Security and Throughput in Wireless Networks , 2007, IEEE Transactions on Dependable and Secure Computing.

[24]  Chong Li,et al.  Distributed Rate and Power Control in Vehicular Networks , 2015, ArXiv.

[25]  A. Goldsmith,et al.  Capacity of Nakagami multipath fading channels , 1997, 1997 IEEE 47th Vehicular Technology Conference. Technology in Motion.

[26]  Richard H. Sherman,et al.  Chaotic communications in the presence of noise , 1993, Optics & Photonics.

[27]  Xiao Lu,et al.  Adaptive power management for wireless base stations in a smart grid environment , 2012, IEEE Wireless Communications.

[28]  Sherali Zeadally,et al.  Vehicular ad hoc networks (VANETS): status, results, and challenges , 2010, Telecommunication Systems.

[29]  Jean-Pierre Hubaux,et al.  Game Theory in Wireless Networks: A Tutorial , 2006 .

[30]  Tao Tang,et al.  Joint security and QoS provisioning in cooperative vehicular ad hoc networks , 2013, 2013 IEEE International Conference on Communications (ICC).

[31]  S. Kim Adaptive online power control scheme based on the evolutionary game theory , 2011, IET Commun..

[32]  A. Goldsmith,et al.  Capacity of Rayleigh fading channels under different adaptive transmission and diversity-combining techniques , 1999, IEEE Transactions on Vehicular Technology.

[33]  Paolo Santi,et al.  Approximation Algorithms for Wireless Link Scheduling With SINR-Based Interference , 2010, IEEE/ACM Transactions on Networking.

[34]  Jochen Schiller,et al.  Mobile Communications , 1996, IFIP — The International Federation for Information Processing.

[35]  C.E. Shannon,et al.  Communication in the Presence of Noise , 1949, Proceedings of the IRE.

[36]  Zhen Ji,et al.  Optimization between security and delay of quality-of-service , 2011, J. Netw. Comput. Appl..

[37]  Bin Liu,et al.  AHP and game theory based approach for network selection in heterogeneous wireless networks , 2014, 2014 IEEE 11th Consumer Communications and Networking Conference (CCNC).

[38]  Brahmjit Singh,et al.  Performance Evaluation of Security-Throughput Tradeoff with Channel Adaptive Encryption , 2013 .

[39]  Xingming Sun,et al.  Toward Efficient Multi-Keyword Fuzzy Search Over Encrypted Outsourced Data With Accuracy Improvement , 2016, IEEE Transactions on Information Forensics and Security.

[40]  Dingde Jiang,et al.  An evolutionary game theory-based channel access mechanism for wireless multimedia sensor network with rate-adaptive applications , 2016, Multimedia Tools and Applications.

[41]  Hanwen Cao,et al.  A 5G V2X testbed for cooperative automated driving , 2016, 2016 IEEE Vehicular Networking Conference (VNC).