Results 31 to 40 of about 36,856 (154)

Guaranteed False Data Injection Attack Without Physical Model

IEEE Open Access Journal of Power and Energy
Smart grids are increasingly vulnerable to False Data Injection Attacks (FDIAs) due to their growing reliance on interconnected digital systems. Many existing FDIA techniques assume access to critical physical model information, such as grid topology, to
Chenhan Xiao, Napoleon Costilla-Enriquez, Yang Weng   +2 more
doaj   +1 more source

Distribution System State Estimation and False Data Injection Attack Detection with a Multi-Output Deep Neural Network

Energies, 2023
Distribution system state estimation (DSSE) has been introduced to monitor distribution grids; however, due to the incorporation of distributed generations (DGs), traditional DSSE methods are not able to reveal the operational conditions of active ...
Sepideh Radhoush, Trevor C. Vannoy, Kaveen Liyanage, Bradley M. Whitaker, H. Nehrir   +4 more
semanticscholar   +1 more source

Cyber Attack Detection Based on Wavelet Singular Entropy in AC Smart Islands: False Data Injection Attack

IEEE Access, 2021
Since Smart-Islands (SIs) with advanced cyber-infrastructure are incredibly vulnerable to cyber-attacks, increasing attention needs to be applied to their cyber-security.
Moslem Dehghani, Mohammad Ghiasi, Taher Niknam, Abdollah Kavousi-Fard, Elham Tajik, Sanjeevikumar Padmanaban, Hamdulah Aliev   +6 more
doaj   +1 more source

Observer-based false data injection attack resilient event-triggered control of microgrid load frequency control system.

ISA transactions
This study develops a secondary attack resilient observer-based event-triggered control (AROETC) strategy to counter false data injection (FDI) attack at the secondary measurement channel of an islanded microgrid load frequency control (LFC) system with ...
Athira M. Mohan, N. Meskin
semanticscholar   +1 more source

Detection of False Data Injection Attack in Connected and Automated Vehicles via Cloud-Based Sandboxing

IEEE transactions on intelligent transportation systems (Print), 2022
In recent years, developments in vehicle-to-everything communication (V2X) have steadily increased in applications such as platooning and collision avoidance. V2X provides vehicles with long-range information regarding traffic congestion and routing, but
Chunheng Zhao, J. S. Gill, P. Pisu, Gurcan Comert   +3 more
semanticscholar   +1 more source

A Novel Sparse Attack Vector Construction Method for False Data Injection in Smart Grids

Energies, 2020
To improve the security of smart grids (SGs) by finding the system vulnerability, this paper investigates the sparse attack vectors’ construction method for malicious false data injection attack (FDIA).
Meng Xia, Dajun Du, Minrui Fei, Xue Li, Taicheng Yang   +4 more
doaj   +1 more source

Impact of optimal false data injection attacks on local energy trading in a residential microgrid

ICT Express, 2018
This paper illustrates the vulnerability of local energy trading to false data injection attacks in a smart residential microgrid and demonstrates the impact of such attacks on the financial benefits earned by the participants.
Shama N. Islam, M.A. Mahmud, A.M.T. Oo
doaj   +1 more source

Detection of False Data Injection Attack in AGC System Based on Random Forest

Machines, 2023
False data injection attacks change the control effect of automatic generation control systems, which may cause a destructive impact on power systems. In this paper, the data from the regular operation of a system and the data from false data injection ...
Zhengwei Qu, Xinran Zhang, Yuchen Gao, Chao Peng, Yunjing Wang, Popov Maxim Georgievitch   +5 more
doaj   +1 more source

Modified Red Fox Optimizer With Deep Learning Enabled False Data Injection Attack Detection

IEEE Access, 2023
Recently, power systems are drastically developed and shifted towards cyber-physical power systems (CPPS). The CPPS involve numerous sensor devices which generates enormous quantities of information. The data gathered from each sensing component needs to
Hayam Alamro, Khalid Mahmood, Sumayh S. Aljameel, Ayman Yafoz, Raed Alsini, Abdullah Mohamed   +5 more
doaj   +1 more source

An Efficient Privacy-Enhancing Cross-Silo Federated Learning and Applications for False Data Injection Attack Detection in Smart Grids

IEEE Transactions on Information Forensics and Security, 2023
Federated Learning is a prominent machine learning paradigm which helps tackle data privacy issues by allowing clients to store their raw data locally and transfer only their local model parameters to an aggregator server to collaboratively train a ...
Hong-Yen Tran, Jian-Kun Hu, Xuefei Yin, H. Pota   +3 more
semanticscholar   +1 more source