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How to Secure Distr...
How to Secure Distributed Filters Under Sensor Attacks
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- He, Xingkang (author)
- KTH,Reglerteknik,ACCESS Linnaeus Centre
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Ren, X. (author)
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- Sandberg, Henrik (author)
- KTH,ACCESS Linnaeus Centre,Reglerteknik
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- Johansson, Karl H., 1967- (author)
- KTH,Reglerteknik,ACCESS Linnaeus Centre
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(creator_code:org_t)
- Institute of Electrical and Electronics Engineers (IEEE), 2021
- 2021
- English.
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In: IEEE Transactions on Automatic Control. - : Institute of Electrical and Electronics Engineers (IEEE). - 0018-9286 .- 1558-2523. ; , s. 1-1
- Related links:
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Subject headings
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- We study how to secure distributed filters for linear time-invariant systems with bounded noise under false-data injection attacks. A malicious attacker is able to arbitrarily manipulate the observations for a time-varying and unknown subset of the sensors. We first propose a recursive distributed filter consisting of two steps at each update. The first step employs a saturation-like scheme, which gives a small gain if the innovation is large corresponding to a potential attack. The second step is a consensus operation of state estimates among neighboring sensors. We prove the estimation error is upper bounded if the parameters satisfy a condition. We further analyze the feasibility of the condition and connect it to sparse observability in the centralized case. When the attacked sensor set is known to be time-invariant, the secured filter is modified by adding an online local attack detector. The detector is able to identify the attacked sensors whose observation innovations are larger than the detection thresholds. Also, with more attacked sensors being detected, the thresholds will adaptively adjust to reduce the space of the stealthy attack signals.
Subject headings
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Reglerteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Control Engineering (hsv//eng)
Keyword
- Detectors
- Estimation error
- Observability
- Observers
- Robustness
- Technological innovation
- Upper bound
- Invariance
- Linear systems
- Detection threshold
- Distributed filters
- Estimation errors
- False data injection attacks
- Linear time invariant systems
- Potential attack
- State estimates
- Time invariants
- Time varying control systems
Publication and Content Type
- ref (subject category)
- art (subject category)
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