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• W2072305722 abstract "A novel technique to detect injection attacks in linear time invariant systems is proposed. Detection involves the use of a cross-correlator that dynamically increases its analysis window to increase the probability of detection. For correlation analysis and potential remediation, the cross-correlator makes reference to a linear (internal) model of the system sensor. Unlike some existing techniques, it does not require the construction of a complex internal model of the entire control system, pre-knowledge of the attacking signal characteristics or perturbation of the control system. Performance simulations show probabilities of detection that can reach 100% with bounded analysis window size. Sensitivity analysis also show that the cross-correlator exhibits good robustness against unlikely to occasional transient sensor failures." @default.
• W2072305722 created "2016-06-24" @default.
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• W2072305722 date "2013-11-01" @default.
• W2072305722 modified "2023-10-16" @default.
• W2072305722 title "Detecting injection attacks in linear time invariant systems" @default.
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• W2072305722 doi "https://doi.org/10.1109/iccis.2013.6751583" @default.
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