Detecting False Data Injection Attacks on Power Grid by Sparse Optimization

By Lanchao Liu, Mohammad Esmalifalak, Q. Ding, V. A. Emesih, Zhu Han. IEEE Transactions on Smart Grid, 2014

403 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Control and Systems Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/8af1284fe95ec5a2782f024dc9f78f11109a864c

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Citations in the corpus

Online False Data Injection Attack Detection With Wavelet Transform and Deep Neural Networks (2018, methodology): “Specifically, the methods proposed in [18] and [19] are implemented and tested with the same data.”
A Novel Data Fusion Algorithm to Combat False Data Injection Attacks in Networked Radar Systems (2018, methodology): “[29] presented a detection approach for power grid .”
Security and Privacy in the Internet of Things (2017, background): “Various schemes have been proposed to secure IoT communication and data exchange, which span over a variety of topics including but not limited to privacy-preserving data collection [102, 111], detection and prevention of false data injection [101, 110, 80, 158], patient monitoring [127, 112], etc.”
Real-Time Detection of False Data Injection Attacks in Smart Grid: A Deep Learning-Based Intelligent Mechanism (2017, methodology): “[8] developed an FDI detection mechanism by using the properties of the low dimensionality of measurements and sparsity of attacks.”
A Survey on the Detection Algorithms for False Data Injection Attacks in Smart Grids (2020, methodology): “Matrix separation (MS) was introduced in [77], [78] where the detection of the FDIA is based on the separation of nominal power grid states and anomalies matrices assuming the sparse nature of the FDIA.”
A Review of False Data Injection Attacks Against Modern Power Systems (2017, methodology): “[43] consider the detection problem as a matrix separation problem, and proposed nuclear norm minimization method and low rank matrix factorization approach.”
Detecting False Data Injection Attacks in AC State Estimation (2015, background): “2) Detection-Based Approaches: Another type of countermeasure proposed by [14]–[16] is to detect potential false data injection attacks using Bayesian framework.”