Modified Matrix Completion-Based Detection of Stealthy Data Manipulation Attacks in Low Observable Distribution Systems

James Ranjith Kumar Rajasekaran*, Balasubramaniam Natarajan, Anil Pahwa

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


A composite detection technique against stealthy data manipulations is developed in this paper for distribution networks that are low observable. Attack detection strategies typically rely on state estimation which becomes challenging when limited measurements are available. In this paper, a modified matrix completion approach provides estimates of the system state and its error variances for the locations in the network where measurements are unavailable. Using the error statistics and their corresponding state estimates, bad data detection can be carried out using the chi-squared test. The proposed approach employs a moving target defence strategy (MTD) where the network parameters are perturbed through distributed flexible AC transmission system (D-FACTS) devices such that stealthy data manipulation attacks can be exposed in the form of bad data. Thus, the bad data detection approach developed in this paper can detect stealthy attacks using the MTD strategy. This technique is implemented on 37-bus and 123-bus three-phase unbalanced distribution networks to demonstrate the attack detection accuracy even for a low observable system.
Original languageEnglish
Pages (from-to)4851-4862
Number of pages12
JournalIEEE Transactions on Smart Grid
Issue number6
Early online date13 Apr 2023
Publication statusPublished - 1 Nov 2023
Externally publishedYes

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