Collaborative Research: CPS: Medium: Sensor Attack Detection and Recovery in Cyber-Physical Systems

合作研究：CPS：中：网络物理系统中的传感器攻击检测和恢复

• 批准号: 2143256
• 负责人: Fanxin Kong
• 金额: $ 50万
• 依托单位: Syracuse University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-07-15 至 2023-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2143256&HistoricalAwards=false
• 关键词: Collaborative; Research; CPS; Medium; Sensor

New vulnerabilities arise in Cyber-Physical Systems (CPS) as new technologies are integrated to interact and control physical systems. In addition to software and network attacks, sensor attacks are a crucial security risk in CPS, where an attacker alters sensing information to negatively interfere with the physical system. Acting on malicious sensor information can cause serious consequences. While many research efforts have been devoted to protecting CPS from sensor attacks, several critical problems remain unresolved. First, existing attack detection works tend to minimize the detection delay and false alarms at the same time; this goal, however, is not always achievable due to the inherent trade-off between the two metrics. Second, there has been much work on attack detection, yet a key question remains concerning what to do after detecting an attack. Importantly, a CPS should detect an attack and recover from the attack before irreparable consequences occur. Third, the interrelation between detection and recovery has met with insufficient attention: Integrating detection and recovery techniques would result in more effective defenses against sensor attacks.This project aims to address these key problems and develop novel detection and recovery techniques. The project aims to achieve timely and safe defense against sensor attacks by addressing real-time adaptive-attack detection and recovery in CPS. First, this project explores new attack detection techniques that can dynamically balance the trade-off between the detection delay and the false-alarm rate in a data-driven fashion. In this way, the detector will deliver attack detection with predictable delay and maintain the usability of the detection approach. Second, this project pursues new recovery techniques that bring the system back to a safe state before a recovery deadline while minimizing the degradation to the mission being executed by the system. Third, this project investigates efficient techniques that address the attack detection and recovery in a coordinated fashion to significantly improve response to attacks. Specific research tasks include the development of real-time adaptive sensor attack detection techniques, real-time attack recovery techniques, and attack detection and recovery coordination techniques. The developed techniques will be implemented and evaluated on multiple CPS simulators and an autonomous vehicle testbed.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

随着新技术的集成，网络物理系统（CPS）中出现了新的漏洞，以交互和控制物理系统。除了软件和网络攻击之外，传感器攻击也是CPS中的一个重要安全风险，攻击者会改变传感信息，从而对物理系统产生负面干扰。对恶意传感器信息采取行动可能会导致严重后果。虽然许多研究工作已经致力于保护CPS免受传感器攻击，但仍有一些关键问题尚未解决。首先，现有的攻击检测工作往往最大限度地减少检测延迟和误报在同一时间，这个目标，但是，并不总是可以实现的，由于这两个指标之间的固有的权衡。第二，在攻击检测方面已经做了很多工作，但一个关键问题仍然是检测到攻击后该怎么做。重要的是，CPS应该检测攻击并在发生不可挽回的后果之前从攻击中恢复。 第三，检测和恢复之间的相互关系没有得到足够的重视：将检测和恢复技术结合起来可以更有效地防御传感器攻击。本项目旨在解决这些关键问题，并开发新的检测和恢复技术。该项目旨在通过解决CPS中的实时自适应攻击检测和恢复来实现对传感器攻击的及时和安全防御。首先，该项目探索了新的攻击检测技术，可以动态地平衡检测延迟和误报率之间的权衡在数据驱动的方式。 这样，检测器将以可预测的延迟提供攻击检测，并保持检测方法的可用性。其次，该项目追求新的恢复技术，使系统恢复到安全状态之前的恢复期限，同时最大限度地减少退化的使命正在执行的系统。第三，该项目研究了以协调方式解决攻击检测和恢复的有效技术，以显着提高对攻击的响应。具体的研究任务包括开发实时自适应传感器攻击检测技术、实时攻击恢复技术以及攻击检测和恢复协调技术。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Fail-Safe: Securing Cyber-Physical Systems against Hidden Sensor Attacks

故障安全：保护网络物理系统免受隐藏传感器攻击

• DOI: 10.1109/rtss55097.2022.00029
• 发表时间: 2022
• 期刊: 2022 IEEE Real-Time Systems Symposium (RTSS
• 作者: Liu, Mengyu;Zhang, Lin;Lu, Pengyuan;Sridhar, Kaustubh;Kong, Fanxin;Sokolsky, Oleg;Lee, Insup
• 通讯作者: Lee, Insup

Real-Time Data-Predictive Attack-Recovery for Complex Cyber-Physical Systems

复杂网络物理系统的实时数据预测攻击恢复

• 发表时间: 2023
• 期刊: 29th IEEE Real-Time and Embedded Technology and Applications Symposium
• 作者: Zhang, Lin;Sridhar, Kaustubh;Liu, Mengyu;Lu, Pengyuan;Chen, Xin;Kong, Fanxin;Sokolsky, Oleg;Lee, Insup
• 通讯作者: Lee, Insup

Variable Window and Deadline-Aware Sensor Attack Detector for Automotive CPS

• DOI: 10.1109/isorc58943.2023.00018
• 发表时间: 2023-05
• 期刊: 2023 IEEE 26th International Symposium on Real-Time Distributed Computing (ISORC)
• 作者: Francis Akowuah;Kenneth Fletcher;Fanxin Kong

Work-in-Progress: Optimal Checkpointing Strategy for Real-time Systems with Both Logical and Timing Correctness

正在进行的工作：具有逻辑和时序正确性的实时系统的最佳检查点策略

• DOI: 10.1109/rtss55097.2022.00055
• 发表时间: 2022
• 期刊: 2022 IEEE Real-Time Systems Symposium (RTSS
• 作者: Zhang, Lin;Wang, Zifan;Kong, Fanxin
• 通讯作者: Kong, Fanxin

Optimal Checkpointing Strategy for Real-time Systems with Both Logical and Timing Correctness

具有逻辑和时序正确性的实时系统的最佳检查点策略

• DOI: 10.1145/3603172
• 发表时间: 2023
• 期刊: ACM Transactions on Embedded Computing Systems
• 影响因子: 2
• 作者: Zhang, Lin;Wang, Zifan;Kong, Fanxin
• 通讯作者: Kong, Fanxin