4.7 Article

A Switching Multiplicative Watermarking Scheme for Detection of Stealthy Cyber-Attacks

Journal

IEEE TRANSACTIONS ON AUTOMATIC CONTROL
Volume 66, Issue 6, Pages 2558-2573

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TAC.2020.3013850

Keywords

Watermarking; Authentication; Switches; Atmospheric measurements; Particle measurements; Cryptography; Digital filters; equalizers; intrusion detection; security; watermarking

Funding

  1. European Union [608224]
  2. EU [707546]
  3. Swedish Research Council [2018-04396]
  4. Swedish Foundation for Strategic Research
  5. Marie Curie Actions (MSCA) [707546] Funding Source: Marie Curie Actions (MSCA)

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This article proposes a watermarking approach for detecting stealthy attacks on sensor measurements, ensuring data verification and source authentication. Designing watermark filters and a switching protocol guarantees the performance and stability of the watermark scheme to allow for detectable cyber-attacks.
This article addresses the detection of stealthy attacks on sensor measurements. Inspired in authentication schemes with weak cryptographic guarantees, we propose a watermarking approach to validate the data and its source. In particular, we propose a multiplicative scheme, where the sensor outputs are watermarked by a bank of filters, then transmitted through the possibly unsecured communication network. The original measurement data are finally reconstructed by a watermark remover. To allow the detection of replay attacks, the watermarking filters are devised as hybrid switching systems, whose parameters are assumed to be unknown to the adversary. Design rules are provided, guaranteeing that the nominal closed-loop performance is not deteriorated by the watermarking scheme and ensuring robust stability with mismatched filter parameters. Moreover, we design a switching protocol with no communication overhead to allow the watermarking filters to synchronously update their parameters. The detectability properties of cyber-attacks are analyzed, and the results are illustrated through numerical examples for replay and data injection attacks.

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