| NSF Org: |
CNS Division Of Computer and Network Systems |
| Recipient: |
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| Initial Amendment Date: | July 20, 2015 |
| Latest Amendment Date: | July 20, 2015 |
| Award Number: | 1505664 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Ralph Wachter
rwachter@nsf.gov (703)292-8950 CNS Division Of Computer and Network Systems CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | July 15, 2015 |
| End Date: | June 30, 2019 (Estimated) |
| Total Intended Award Amount: | $500,000.00 |
| Total Awarded Amount to Date: | $500,000.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
201 OLD MAIN UNIVERSITY PARK PA US 16802-1503 (814)865-1372 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
PA US 16802-7000 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): |
CPS-Cyber-Physical Systems, Secure &Trustworthy Cyberspace |
| Primary Program Source: |
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| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.070 |
ABSTRACT
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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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
Cyber-physical systems (CPS) integrate information and communications technology (ICT) systems into physical systems. Inherent vulnerabilities of ICT systems impose significant security threats on CPS. Existing cyber defenses alone are not sufficient to secure CPS. For example, existing intrusion detection systems (IDS) cannot detect attacks launched from physical channels; e.g., GPS spoofing, since no abnormal cyberspace behavior is triggered and captured. In addition, existing cyber defenses do not provide intrusion responses for physical systems against cyberattacks.
In this project, we developed control-theoretic approaches to complement existing cyber defenses. In particular, we developed a set of algorithms for intrusion detection of linear and nonlinear dynamic systems subject to sensor attacks, actuator attacks and switching attacks. The proposed algorithms can detect occurrence of attacks, localize the attacks and further correctly estimate states and mode of dynamic systems as well as actions of attackers. Estimation errors and stability were formally analyzed using Lyapunov theory and information theory.
We implemented the developed control-theoretic IDS on two types of mobile robots and evaluated detection performance against various misbehavior scenarios, including signal interference, sensor spoofing, logic bomb and physical jamming. Both evaluations showed less than 3% of false positive rate and less than 1% of false negative detection rate on average. Detection delays remained within an average of 0.40s. In addition, we developed a collaborative IDS for detection of sensor and actuator attacks in connected urban vehicles. The IDS fuses local sensing information and that from nearby vehicles to enhance detection capabilities. We implemented a prototype detection system on a scaled autonomous vehicle testbed and evaluated the system regarding the effectiveness under different attacks launched through multiple attack channels. The experimental results demonstrated detection capabilities under destructive attack cases when all sensors in a vehicle were compromised.
Besides IDS, we developed attack-resilient distributed formation control algorithms for vehicle-operator networks against denial-of-service attacks and replay attacks. We showed that input and state constraints were always enforced, and desired formation can be asymptotically achieved provided that the union of communication graphs between operators satisfied certain connectivity assumption.
To summarize, this project leveraged control theory to develop holistic and provably correct algorithms for intrusion detection and response against cyberattacks on CPS. The developed results are applicable to many engineering systems, including self-driving cars, mobile robots, smart grid, smart buildings and intelligent transportation systems.
Last Modified: 09/28/2019
Modified by: Minghui Zhu
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