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BLCS: Brain-Like Distributed Control Security in Cyber Physical Systems

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The cyber-physical system (CPS) has operated, controlled, and coordinated the physical systems integrated by a computing and communication core applied in Industry 4.0. To accommodate CPS services, fog radio and… Click to show full abstract

The cyber-physical system (CPS) has operated, controlled, and coordinated the physical systems integrated by a computing and communication core applied in Industry 4.0. To accommodate CPS services, fog radio and optical networks (F-RON) has become an important supporting physical cyber infrastructure taking advantage of both the inherent ubiquity of wireless technology and the large capacity of optical networks. However, cyber security is the biggest issue in the CPS scenario as there is a trade-off between security control and privacy exposure in F-RON. To deal with this issue, we propose a brain-like distributed control security (BLCS) architecture for F-RON in CPS by introducing a brain-like security (BLS) scheme. BLCS can accomplish the secure cross-domain control among tripartite controllers verification in the scenario of decentralized F-RON for distributed computing and communications, which has no need to disclose the private information of each domain against cyber-attacks. BLS utilizes parts of information to perform control identification through a relation network and a deep learning of behavior library. The functional modules of BLCS architecture are illustrated including various controllers and a brain-like knowledge base. The interworking procedures in distributed control security modes based on BLS are described. The overall feasibility and efficiency of the architecture are experimentally verified on a software defined network testbed in terms of average mistrust rate, path provisioning latency, packet loss probability, and blocking probability. The emulation results are obtained and dissected based on the testbed.

Keywords: brain like; control security; control; security; distributed control

Journal Title: IEEE Network
Year Published: 2020

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