Cyber-physical systems encounter privacy and security challenges due to the intricate relation between involved components and the vulnerability of wireless communication. Both passive privacy divulgence and active malicious sabotage may degrade the system estimation performance. In this thesis, privacy- and security-aware remote state estimation is studied. Specifically, we propose a privacy-aware multi-party state estimation paradigm, investigate reset attacks and time synchronization attacks, and analyze the state estimation under these attacks, respectively.

First, with the awareness of protecting participants' data and model privacy, we develop a multi-party state estimation paradigm for the scenario where multiple parties monitor a physical plant by deploying their own s...[ Read more ]

Cyber-physical systems encounter privacy and security challenges due to the intricate relation between involved components and the vulnerability of wireless communication. Both passive privacy divulgence and active malicious sabotage may degrade the system estimation performance. In this thesis, privacy- and security-aware remote state estimation is studied. Specifically, we propose a privacy-aware multi-party state estimation paradigm, investigate reset attacks and time synchronization attacks, and analyze the state estimation under these attacks, respectively.

First, with the awareness of protecting participants' data and model privacy, we develop a multi-party state estimation paradigm for the scenario where multiple parties monitor a physical plant by deploying their own sensor networks and update the state estimate according to the average state estimate of all the parties calculated by a cloud server and security module. The paradigm utilizes additively homomorphic encryption to preserve the data privacy. Meanwhile, all the parties collaboratively develop a state (or optimal) fusion rule without disclosing sensitive model information. We analyze the stabilization, estimation performance, and the optimality of the proposed paradigm. Second, for the reset attacks which reset the a priori state estimate at the remote estimator, basic and advanced reset attacks with different objectives and attacking capabilities are introduced. We investigate the attack impacts on state estimation performance. Finally, for the time synchronization attacks that disturb the sensor clocks in a multi-system scheduling scenario, we analyze the attack effectiveness and propose a countermeasure by constructing shift invariant transmission polices.