Secure Enforcement in Cognitive Internet of Vehicles

As for deployment of security strategy, corresponding forwarding rules for switches can be given in allusion to different traffic conditions. However, due to lack of global cognitive control for security strategy deployment in traditional Internet of Vehicles (IoV), it is quite difficult to realize global and optimized security strategy deployment scheme so as to meet security requirements in different traffic conditions. On basis of traditional IoV, cognitive engine is added in cognitive IoV (CIoV) to enhance the intelligence of traditional IoV. In allusion to CIoV, and in consideration of restrictions on transmission delay, the security strategy deployment for switches on core network is formulated in this paper, thus not only the safe transmission rules are met, but the transmission delay can also be the lowest. To be specific, the path selection of switches is modeled as 0-1 programming problem in this paper, and that optimization problem is proved to be a nonconvex optimization problem. Then we convert that problem into a convex optimization problem by log-det heuristic algorithm, thus to give path selection scheme to meet security requirements with the lowest delay on the whole. Experiment proves that cognitive engine-based security strategy deployment put forth in this paper is much better than other schemes.

[1]  Nick McKeown,et al.  OpenFlow: enabling innovation in campus networks , 2008, CCRV.

[2]  Shengli Xie,et al.  MixGroup: Accumulative Pseudonym Exchanging for Location Privacy Enhancement in Vehicular Social Networks , 2016, IEEE Transactions on Dependable and Secure Computing.

[3]  Depeng Jin,et al.  Vehicular Fog Computing: A Viewpoint of Vehicles as the Infrastructures , 2016, IEEE Transactions on Vehicular Technology.

[4]  Xiaohui Liang,et al.  Privacy Leakage of Location Sharing in Mobile Social Networks: Attacks and Defense , 2016, IEEE Transactions on Dependable and Secure Computing.

[5]  Mengyuan Li,et al.  You Can Jam But You Cannot Hide: Defending Against Jamming Attacks for Geo-Location Database Driven Spectrum Sharing , 2016, IEEE Journal on Selected Areas in Communications.

[6]  Xiaolong Li,et al.  An attack-and-defence game for security assessment in vehicular ad hoc networks , 2014, Peer Peer Netw. Appl..

[7]  Zhifeng Zhao,et al.  Toward 5G: when explosive bursts meet soft cloud , 2014, IEEE Network.

[8]  Jing Chen,et al.  Dominating Set and Network Coding-Based Routing in Wireless Mesh Networks , 2015, IEEE Transactions on Parallel and Distributed Systems.

[9]  Min Chen,et al.  Green and Mobility-Aware Caching in 5G Networks , 2017, IEEE Transactions on Wireless Communications.

[10]  Jing Chen,et al.  Batch Identification Game Model for Invalid Signatures in Wireless Mobile Networks , 2017, IEEE Transactions on Mobile Computing.

[11]  Kai Wang,et al.  LiveSec: Towards Effective Security Management in Large-Scale Production Networks , 2012, 2012 32nd International Conference on Distributed Computing Systems Workshops.

[12]  Mansour Sheikhan,et al.  Modification of supervised OPF-based intrusion detection systems using unsupervised learning and social network concept , 2017, Pattern Recognit..

[13]  Chih-Fong Tsai,et al.  CANN: An intrusion detection system based on combining cluster centers and nearest neighbors , 2015, Knowl. Based Syst..

[14]  Walid G. Aref,et al.  Casper*: Query processing for location services without compromising privacy , 2006, TODS.

[15]  Quanyan Zhu,et al.  Dependable Demand Response Management in the Smart Grid: A Stackelberg Game Approach , 2013, IEEE Transactions on Smart Grid.

[16]  Haojin Zhu,et al.  Privacy Leakage via De-Anonymization and Aggregation in Heterogeneous Social Networks , 2020, IEEE Transactions on Dependable and Secure Computing.

[17]  Jim Esch,et al.  Software-Defined Networking: A Comprehensive Survey , 2015, Proc. IEEE.

[18]  Min Chen,et al.  Narrow Band Internet of Things , 2017, IEEE Access.

[19]  Ahmed Toumanari,et al.  Survey of Security in Software-Defined Network , 2017 .

[20]  Mohsen Guizani,et al.  Software-Defined Networking for RSU Clouds in Support of the Internet of Vehicles , 2015, IEEE Internet of Things Journal.

[21]  Sasu Tarkoma,et al.  Software defined networking for security enhancement in wireless mobile networks , 2014, Comput. Networks.

[22]  Ziming Zhao,et al.  Uncovering the Face of Android Ransomware: Characterization and Real-Time Detection , 2018, IEEE Transactions on Information Forensics and Security.

[23]  Kang G. Shin,et al.  Fingerprinting Electronic Control Units for Vehicle Intrusion Detection , 2016, USENIX Security Symposium.

[24]  Min Chen,et al.  Data-Driven Computing and Caching in 5G Networks: Architecture and Delay Analysis , 2018, IEEE Wireless Communications.

[25]  Athanasios V. Vasilakos,et al.  Leveraging software-defined networking for security policy enforcement , 2016, Inf. Sci..

[26]  Joseph Mitola,et al.  Cognitive radio: making software radios more personal , 1999, IEEE Wirel. Commun..

[27]  Giancarlo Fortino,et al.  Modeling and Simulating Internet-of-Things Systems: A Hybrid Agent-Oriented Approach , 2017, Computing in Science & Engineering.

[28]  Eylem Ekici,et al.  Vehicular Networking: A Survey and Tutorial on Requirements, Architectures, Challenges, Standards and Solutions , 2011, IEEE Communications Surveys & Tutorials.

[29]  Min Chen,et al.  A 5G Cognitive System for Healthcare , 2017, Big Data Cogn. Comput..

[30]  Cailian Chen,et al.  Speed-Based Location Tracking in Usage-Based Automotive Insurance , 2017, 2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS).

[31]  Fei-Yue Wang,et al.  A Security and Privacy Review of VANETs , 2015, IEEE Transactions on Intelligent Transportation Systems.