Results 61 to 70 of about 702 (166)

Deep learning-based identification of false data injection attacks on modern smart grids

Energy Reports, 2022
With the rapid adoption of renewables within the conventional power grid, the need of real-time monitoring is inevitable. State estimation algorithms play a significant role in defining the current operating scenario of the grid.
Debottam Mukherjee, Samrat Chakraborty, Almoataz Y. Abdelaziz, Adel El-Shahat   +3 more
doaj   +1 more source

Adaptive inverse control for trajectory tracking with dead‐zone nonlinearity under cyberattacks

IET Control Theory &Applications, Volume 19, Issue 1, January/December 2025.
In response to sensor data integrity challenges and security risks in centralized control systems, a distributed framework is proposed for discrete‐time nonlinear systems with unknown dead‐zones at the input. Leveraging decentralized peer‐to‐peer networks, this framework enhances security by securing information exchange without prior knowledge of ...
Farnaz Sabahi
wiley   +1 more source

Active Learning-Based XGBoost for Cyber Physical System Against Generic AC False Data Injection Attacks

IEEE Access, 2020
With the exponential growth of information and communication technology, the traditional power system is gradually evolving into a cyber physical energy system (CPES) with frequently interactions between physical and cyber components.
Wenli Xue, Ting Wu
doaj   +1 more source

Safety Containment Control for Parabolic PDEs

IET Control Theory &Applications, Volume 19, Issue 1, January/December 2025.
This paper investigates the output feedback containment control problem for multi‐agent systems with multiple leaders under denial‐of‐service attacks. In the considered system, all agents are modelled by partial differential equations. ABSTRACT This paper investigates the output feedback containment control problem for multi‐agent systems (MASs) with ...
Guangshi Li
wiley   +1 more source

FDIA Attack Detection Technique for Smart Grids Based on Graph Reconstruction and Spatio-Temporal Joint Modeling [PDF]

E3S Web of Conferences
With the widespread application of smart grids, the false data injection attack (FDIA) has become a major threat to power grid security. Traditional detection methods often have difficulty in effectively identifying such attacks, especially in complex ...
Gao Yuzhang, Xia Jing
doaj   +1 more source

Active Defense Research against False Data Injection Attacks of Power CPS Based on Data-Driven Algorithms

Energies, 2022
The terminal equipment interconnection and the network communication environment are complex in power cyber–physical systems (CPS), and the frequent interaction between the information and energy flows aggravates the risk of false data injection attacks (
Xiaoyong Bo, Zhaoyang Qu, Lei Wang, Yunchang Dong, Zhenming Zhang, Da Wang   +5 more
doaj   +1 more source

Adaptive Quantized Control for Markov Jump Systems Against Multimode False Data Injection Attack

IET Control Theory &Applications, Volume 19, Issue 1, January/December 2025.
This study addresses the adaptive dynamic quantization control problem for MJSs subject to multi‐mode injection attack, which are jointly characterized by a hidden Markov model. An adaptive dynamic quantization strategy is proposed such that the existing controller without quantization can achieve the same control performance under the quantization ...
Yu Huang, Bei Chen, Yugang Niu
wiley   +1 more source

Power Market Cybersecurity and Profit-targeting Cyberattacks [PDF]

, 2022
The COVID-19 pandemic has forced many companies and business to operate through remote platforms, which has made everyday life and everyone more digitally connected than ever before.
Zhang, Qiwei
core   +1 more source

Cyber–Physical–Social Security of High‐DER‐Penetrated Smart Grids: Threats, Countermeasures, and Challenges

IET Information Security, Volume 2025, Issue 1, 2025.
With the trend of large‐scale renewable distributed energy sources (DERs) penetrating into the smart grids (SGs), the SGs entail heavy reliance on information and communication technologies (ICT) and increasing impact of social behaviors on system operation and management. The SGs can be viewed as cyber–physical–social systems (CPSSs).
Qiuyu Lu, Jun’e Li, Zhao Peng, Ming Ni, Guowen Xu   +4 more
wiley   +1 more source

Leveraging Meta‐Learning for Enhanced False Data Injection Detection in Smart Grids: The ONF‐ML Approach

IET Renewable Power Generation, Volume 19, Issue 1, January/December 2025.
The optimized neuro‐fuzzy meta‐learning (ONF‐ML) model addresses the limitations of existing machine‐learning approaches in detecting false data injection (FDI) intrusions in smart grids. By combining hyperparameter optimization and simulated annealing, ONF‐ML significantly improves detection rates, achieving 91.7% and 81.9% for intrusion samples and ...
Mohammadreza Pourshirazi, Mohsen Simab, Alireza Mirzaee, Bahador Fani   +3 more
wiley   +1 more source