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Breakthrough: CPS-Security: Towards Provably Correct Distributed Attack-Resilient Control of Unmanned-Vehicle-Operator Networks

Breakthrough: CPS-Security: Towards Provably Correct Distributed Attack-Resilient Control of Unmanned-Vehicle-Operator Networks
突破:CPS 安全:实现无人驾驶车辆运营商网络的可证明正确的分布式抗攻击控制
批准号:
1505664
负责人:
Minghui Zhu
金额:
$50.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2015
资助国家:
美国
项目状态:
已结题
起止时间:
2015-07-15 至 2019-06-30

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中文摘要
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英文摘要
Inherent vulnerabilities of information and communication technology systems to cyber-attacks (e.g., malware) impose significant security risks to Cyber-Physical Systems (CPS). This is evidenced by a number of recent accidents. Noticeably, current distributed control of CPS is not really attack-resilient (ensuring task completion despite attacks). Although provable resilience would significantly lift the trustworthiness of CPS, existing defenses are rather ad-hoc and mainly focus on attack detection. In addition, while network attacks have been extensively studied, resilient-to-malware distributed control has been rarely investigated.This project aims to bridge the gap. It aims to investigate provably correct distributed attack-resilient control of CPS. The project will focus on a representative class of CPS, namely unmanned-vehicle-operator networks, and its four main research thrusts are: (1) The development of a distributed attack-resilient control framework to ensure task completion of multiple vehicles despite network attacks and malware attacks, (2) The synthesis of novel distributed attack-resilient control algorithms to deal with network attacks, (3) The design of estimation algorithms to detect malware attacks on vehicles, and computationally efficient algorithms which allow clean vehicles to avoid the collision with the vehicles compromised by malware, and (4) The validation of the cost-effectiveness of the proposed distributed attack-resilient control framework via a principled systematic evaluation plan.The research findings profoundly impact CPS security of a variety of engineering disciplines beyond unmanned-vehicle-operator networks, including smart grid, smart buildings and intelligent transportation systems. The proposed research is interdisciplinary and involves interactions among security, control, distributed algorithms and robotics. This will lead to educational and training opportunities that cross traditional disciplinary boundaries for high-school, undergraduate and graduate students in STEM.
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会议论文
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Data-driven distributed control of mobile robotic networks: Where machine learning meets game theory
国内基金
海外基金
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