Visible to the public Biblio

Filters: Keyword is protocol aware strategy  [Clear All Filters]
2020-10-06
Tomić, Ivana, Breza, Michael J., Jackson, Greg, Bhatia, Laksh, McCann, Julie A..  2018.  Design and Evaluation of Jamming Resilient Cyber-Physical Systems. 2018 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData). :687—694.

There is a growing movement to retrofit ageing, large scale infrastructures, such as water networks, with wireless sensors and actuators. Next generation Cyber-Physical Systems (CPSs) are a tight integration of sensing, control, communication, computation and physical processes. The failure of any one of these components can cause a failure of the entire CPS. This represents a system design challenge to address these interdependencies. Wireless communication is unreliable and prone to cyber-attacks. An attack upon the wireless communication of CPS would prevent the communication of up-to-date information from the physical process to the controller. A controller without up-to-date information is unable to meet system's stability and performance guarantees. We focus on design approach to make CPSs secure and we evaluate their resilience to jamming attacks aimed at disrupting the system's wireless communication. We consider classic time-triggered control scheme and various resource-aware event-triggered control schemes. We evaluate these on a water network test-bed against three jamming strategies: constant, random, and protocol aware. Our test-bed results show that all schemes are very susceptible to constant and random jamming. We find that time-triggered control schemes are just as susceptible to protocol aware jamming, where some event-triggered control schemes are completely resilient to protocol aware jamming. Finally, we further enhance the resilience of an event-triggered control scheme through the addition of a dynamical estimator that estimates lost or corrupted data.