Proactive Flexible Interval Intermittent Jamming for WAVE-Based Vehicular Networks

In this paper, we deal with the eavesdropping issue in Wireless Access in Vehicular Environments- (WAVE-) based vehicular networks. A proactive flexible interval intermittent jamming (FIJ) approach is proposed which predicts the time length T of the physical layer packet to be transmitted by the legitimate user and designs flexible jamming interval (JI) and jamming-free interval (JF) based on the predicted T . Our design prevents eavesdroppers from overhearing the information with low energy cost since the jamming signal is transmitted only within JI. Numerical analysis and simulation study validate the performance of our proactive FIJ, in terms of jamming energy cost and overhearing defense, by comparing with the existing intermittent jamming (IJ) and FIJ.

[1]  Esther M. Arkin,et al.  Secure communication through jammers jointly optimized in geography and time , 2017, Pervasive Mob. Comput..

[2]  Andreas Ziegler,et al.  Risk estimation and risk prediction using machine-learning methods , 2012, Human Genetics.

[3]  Marwan Krunz,et al.  Distributed Power Control in Single-Stream MIMO Wiretap Interference Networks With Full-Duplex Jamming Receivers , 2019, IEEE Transactions on Signal Processing.

[4]  Isabelle Guyon,et al.  Automatic Capacity Tuning of Very Large VC-Dimension Classifiers , 1992, NIPS.

[5]  Ming Li,et al.  Friendly Jamming for Secure Localization in Vehicular Transportation , 2014, SecureComm.

[6]  Mohamed Azab,et al.  Survey on Security Issues in Vehicular Ad Hoc Networks , 2015 .

[7]  Jing Li,et al.  A Lightweight Privacy-Preserving Protocol for VANETs Based on Secure Outsourcing Computing , 2019, IEEE Access.

[8]  Yingshu Li,et al.  Collective Data-Sanitization for Preventing Sensitive Information Inference Attacks in Social Networks , 2018, IEEE Transactions on Dependable and Secure Computing.

[9]  Xiaoshuang Xing,et al.  Joint design of jammer selection and beamforming for securing MIMO cooperative cognitive radio networks , 2017, IET Commun..

[10]  Anis Laouiti,et al.  VANet security challenges and solutions: A survey , 2017, Veh. Commun..

[11]  Jalel Ben-Othman,et al.  Survey on VANET security challenges and possible cryptographic solutions , 2014, Veh. Commun..

[12]  Zhihua Xia,et al.  A VANET privacy protection scheme based on fair blind signature and secret sharing algorithm , 2017 .

[13]  Reza Fotohi,et al.  A New Approach for Improvement Security against DoS Attacks in Vehicular Ad-hoc Network , 2020, International Journal of Advanced Computer Science and Applications.

[14]  M. S. Sudhakar,et al.  Fuzzy curvilinear path optimization using fuzzy regression analysis for mid vehicle collision detection and avoidance system analyzed on NGSIM I-80 dataset (real-road scenarios) , 2019, Neural Computing and Applications.

[15]  V. Vapnik.  Pattern recognition using generalized portrait method , 1963 .

[16]  Chintha Tellambura,et al.  Wireless-Powered Full-Duplex Relay and Friendly Jamming for Secure Cooperative Communications , 2019, IEEE Transactions on Information Forensics and Security.

[17]  Rongqing Zhang,et al.  Cooperative Jamming for Secure UAV Communications With Partial Eavesdropper Information , 2019, IEEE Access.