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dc.contributor.authorMa, L-
dc.contributor.authorWang, Z-
dc.contributor.authorHan, QL-
dc.contributor.authorLam, HK-
dc.identifier.citationIEEE Sensors Journal, 2017, 17 (7), pp. 2279 - 2288en_US
dc.description.abstractThis paper is concerned with the variance-constrained distributed filtering problem for a class of time-varying systems subject to multiplicative noises, unknown but bounded disturbances and deception attacks over sensor networks. The available measurements at each sensing node are collected not only from the individual sensor but also from its neighbors according to the given topology. A new deception attack model is proposed where the malicious signals are injected by the adversary into both control and measurement data during the process of information transmission via the communication network. By resorting to the recursive linear matrix inequality approach, a sufficient condition is established for the existence of the desired filter satisfying the prespecified requirements on the estimation error variance. Subsequently, an optimization problem is formulated in order to seek the filter parameters ensuring the locally optimal filtering performance at each time instant. Finally, an illustrative example is presented to demonstrate the effectiveness and applicability of the proposed algorithm.en_US
dc.format.extent2279 - 2288-
dc.subjectDistributed filteringen_US
dc.subjectMultiplicative noisesen_US
dc.subjectDeception attacksen_US
dc.subjectVariance constraintsen_US
dc.subjectSensor networksen_US
dc.subjectUnknown but bounded disturbancesen_US
dc.titleVariance-Constrained Distributed Filtering for Time-Varying Systems With Multiplicative Noises and Deception Attacks Over Sensor Networksen_US
dc.relation.isPartOfIEEE Sensors Journal-
Appears in Collections:Dept of Computer Science Research Papers

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