Results 81 to 90 of about 24,736,965 (159)

Consensus‐Based Ensemble Learning for False Data Injection Attack Detection Utilising Conceptual Dimensionality Reduction and Temporal Changes

IET Smart Grid, Volume 9, Issue 1, January/December 2026.
This paper proposes a new ensemble ML algorithm for detecting FDIAs targeting state estimation. The outputs of common base classifiers of various types are combined in a weighted manner to form a consensus‐based EL (CEL). The suggested data diversification technique for enhancing the detection accuracy focuses on the importance of temporal changes ...
Hassan Manafi, Hamed Delkhosh, Hossein Seifi   +2 more
wiley   +1 more source

Scalable cyber‐physical testbed for cybersecurity evaluation of synchrophasors in power systems

IET Cyber-Physical Systems
This paper presents a synchrophasor‐based real‐time cyber‐physical power system testbed with a novel security evaluation tool, pySynphasor, that can emulate different real attack scenarios on the phasor measurement unit (PMU). The testbed focuses on real‐
Shuvangkar Chandra Das, Tuyen Vu, Herbert Ginn   +2 more
doaj   +1 more source

Detecting False Data Injection Attacks Using Machine Learning-Based Approaches for Smart Grid Networks

Applied Sciences
Current electricity sectors will be unable to keep up with commercial and residential customers’ increasing demand for data-enabled power systems. Therefore, next-generation power systems must be developed.
MD Jainul Abudin, Surmila Thokchom, R. T. Naayagi, Gayadhar Panda   +3 more
doaj   +1 more source

The data recovery strategy on machine learning against false data injection attacks in power cyber physical systems

Measurement + Control
During the transmission of power measurement data through communication networks from remote terminal unit (RTU) to the state estimator in Supervisory Control and Data Acquisition (SCADA), power cyber-physical systems (PCPSs) are more susceptible to ...
Qinxue Li, Xiaofen Yang, Xuhuan Xie, Guiyun Liu   +3 more
doaj   +1 more source

A Hybrid ResNet-iTransformer Model for False Data Injection Attack Detection in Electric Vehicle Fast-Charging Stations

World Electric Vehicle Journal
As a crucial flexible regulation resource in distribution networks, electric vehicle fast-charging stations exhibit high-power, stochastic fluctuation characteristics.
Shiqian Wang, Li Di, Ding Han, Qiuyan Li, Yuanyuan Wang, Dawei Song   +5 more
doaj   +1 more source

Smart Grid Evaluation and Defence of False Data Injection Attacks [PDF]

This work evaluates the impact of the False Data Injection Attack on a smart grid and presents a novel control scheme which can mitigate the impact of the attack through the use of local reactive power measurements and insertion of locally trusted data ...
Martin, Charlie
core   +1 more source

False Data Injection Attack Detection Based on Wavelet Packet Decomposition and Random Forest in Smart Grid

, 2022
As one of the critical infrastructures, the safety and reliability of the smart grid are directly associated with the development and stability of society. However, studies have shown that the power grid is at risk when the parameters are manipulated and
Chen, Zhenyu, Guan, Zhitao, Wu, Longfei, Yuan, Shuai, Du, Xiaojiang   +4 more
core   +1 more source

Test Data Generation for False Data Injection Attack Testing in Air Traffic Surveillance

, 2020
International audienceThe ADS-B --- Automatic Dependent Surveillance Broadcast --- technology requires aircraft to broadcast their position and velocity periodically.
Cretin, Aymeric, Vernotte, Alexandre, Legeard, Bruno, Peureux, Fabien, Chevrot, Antoine   +4 more
core   +2 more sources

Localization Detection of False Data Injection Attacks in Novel Energy and Power Systems Based on Correlated Feature‐Multi‐Label Cascading Boosted Forests

Engineering Reports
Under the dual influence of power system transition to integrated energy and the evolution of cyberattack technology, a correlation feature‐multilabel cascade boosted forest based false data injection attack localization and detection method is proposed ...
Lei Wang, Tong Li, Hongbi Geng, Yang Liu, Jian Chen, Hongwei Zhao   +5 more
doaj   +1 more source

Optimizing CNN-LSTM for the Localization of False Data Injection Attacks in Power Systems

Applied Sciences
As the informatization of power systems advances, the secure operation of power systems faces various potential network attacks and threats. The false data injection attack (FDIA) is a common attack mode that can lead to abnormal system operations and ...
Zhuo Li, Yaobin Xie, Rongkuan Ma, Zihan Wei   +3 more
doaj   +1 more source