Remote State Estimation with Privacy Against Active Eavesdroppers
Matthew Crimson, Justin M. Kennedy, Daniel E. Quevedo

TL;DR
This paper introduces an encoding scheme for cyber-physical systems that enhances privacy against active eavesdroppers by transmitting noise selectively, thereby degrading the eavesdropper's estimation while preserving legitimate user performance.
Contribution
It proposes a novel noise-based encoding scheme activated upon eavesdropper detection, balancing privacy and system performance in insecure network environments.
Findings
The encoding scheme effectively increases the eavesdropper's estimation error.
The scheme maintains acceptable performance levels for the legitimate user.
Numerical examples demonstrate the scheme's practical effectiveness.
Abstract
This paper considers a cyber-physical system under an active eavesdropping attack. A remote legitimate user estimates the state of a linear plant from the state information received from a sensor. Transmissions from the sensor occur via an insecure and unreliable network. An active eavesdropper may perform an attack during system operation. The eavesdropper intercepts transmissions from the sensor, whilst simultaneously sabotaging the data transfer from the sensor to the remote legitimate user to harm its estimation performance. To maintain state confidentiality, we propose an encoding scheme that is activated on the detection of an eavesdropper. Our scheme transmits noise based on a pseudo-random indicator, pre-arranged at the legitimate user and sensor. The transmission of noise harms the eavesdropper's performance, more than that of the legitimate user. Using the proposed encoding…
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Taxonomy
TopicsSmart Grid Security and Resilience · Adversarial Robustness in Machine Learning · Physical Unclonable Functions (PUFs) and Hardware Security
