The focus of the proposed research is to improve our understanding of cyber threats to Cyber Physical System(s) (CPS(s)) and to develop and experiment with strategies to mitigate such threats. Our approach is based on well understood technical foundations borrowed from the interdisciplinary fields of control theory, artificial intelligence, game theory, networking, and software engineering. The techniques we propose will be evaluated against, and demonstrated in, scaled and/or simulated versions of critical CPS in the iTrust lab environment.

The entire research program under iTrust will be carried out in three phases. Phase I will focus on setting up the iTrust lab and initiating two research tracks aimed at (a) modelling and verifying CPS properties and (b) understanding the nature of threats to CPS when sensors and communications networks are compromised. Phase II will expand the research into the area of attack detection using techniques from machine learning and the design of new robust control mechanisms for networked control of CPS. Phase III will aim at integrating the knowledge gained from existing projects and deriving fundamental design principles to be applied when designing new CPS or upgrading the existing ones. This phased approach will enable iTrust researchers to better understand exactly how to focus on CPS security, assist in the set of the iTrust lab, and allow newly hired faculty to also join in the iTrust research program.

TASK TEAM DESCRIPTION
Task 1 Sun Jun
Daniel Jackson
Martin C. Rinard,
Kong Ping Fan,
Nguyen Truong Khanh
Develop and experiment with design strategies and tools for achieving end-to-end resilience to attack.
Task 2 Nils Ole Tippernhauer,
Yuen Chau,
Dau Son Hoang,
Song Wentu
Develop and experiment with trustworthiness and security for data acquisition and communications in CPS.
Task 3 Aditya P. Mathur,
Giedre Sabaliauskaite
Analysis and development of techniques for detecting and responding to attacks on CPS. Intelligent checkers approach for monitoring CPS and identifying cyber-attacks and cross-correlation technique for detecting false data injection attacks.