Results 271 to 280 of about 474,494 (357)

Reinforcement Learning-Based False Data Injection Attacks in Smart Grids

IEEE Transactions on Industrial Informatics
False data injection (FDI) attacks construct attack vectors to inject false data into tampered meters with the goal of falsifying state estimation, but resulting in low successful attack rate with high attack costs in terms of the number of tampered ...
Liang Xiao, Haoyu Chen, Shiyu Xu, Zefang Lv, Chuxuan Wang, Yilin Xiao   +5 more
semanticscholar   +1 more source

LESSON: Multi-Label Adversarial False Data Injection Attack for Deep Learning Locational Detection

IEEE Transactions on Dependable and Secure Computing
Deep learning methods can not only detect false data injection attacks (FDIA) but also locate attacks of FDIA. Although adversarial false data injection attacks (AFDIA) based on deep learning vulnerabilities have been studied in the field of single-label
Jiwei Tian, Chao Shen, Buhong Wang, Xiaofang Xia, Meng Zhang, Chenhao Lin, Qian Li   +6 more
semanticscholar   +1 more source

False data injection on EKF-based navigation control

2017 International Conference on Unmanned Aircraft Systems (ICUAS), 2017
Small consumer unmanned aircraft systems (sUASs) have been involved in many security incidents recently. Current defense methods have serious limitations because they mostly try to physically capture an sUAS or jam its communications and its GPS signals to trigger its fail-safe features.
Wenxin Chen, Zhenhai Duan, Yingfei Dong
openaire   +1 more source

Resilient Cooperative Secondary Control of Islanded AC Microgrids Utilizing Inverter-Based Resources Against State-Dependent False Data Injection Attacks

IEEE transactions on industrial electronics (1982. Print)
In this article, we investigate the impact of potential state-dependent false data injection cyber-attacks on frequency synchronization and active power management in islanded ac microgrids.
Mahmood Jamali, M. Sadabadi, M. Davari, Subham S. Sahoo, F. Blaabjerg   +4 more
semanticscholar   +1 more source

Resilient Distributed Control Against False Data Injection Attacks for Demand Response

IEEE Transactions on Power Systems
To maintain the power system balance, flexible load resources have been widely employed to provide operating reserves, which is named demand response (DR).
Shaohua Yang, Keng-Weng Lao, Yulin Chen, Hongxun Hui   +3 more
semanticscholar   +1 more source

Distributed Data-Driven Control for a Connected Autonomous Vehicle Platoon Subjected to False Data Injection Attacks

IEEE Transactions on Automation Science and Engineering
In this paper, we consider the need for deployment in the long-distance safe longitudinal formation control task when the connected autonomous vehicle (CAV) platoon is subjected to malicious cyber attacks.
Panpan Zhu, S. Jin, Xuhui Bu, Zhongsheng Hou   +3 more
semanticscholar   +1 more source

Resilient Event-Triggered MPC for Load Frequency Regulation With Wind Turbines Under False Data Injection Attacks

IEEE Transactions on Automation Science and Engineering
To further the penetration level of renewable energy sources (RESs) in power systems, the paper integrates wind turbines into conventional load frequency control (LFC). A resilient model predictive control (MPC) framework is constructed in the context of
Zhijian Hu, Rong Su, K. Ling, Yao Guo, Renjie Ma   +4 more
semanticscholar   +1 more source

Consensus-based filtering under false data injection attacks

European Journal of Control, 2019
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Xia, Yuanyuan, Yang, Wen, Zhao, Zhiyun
openaire   +2 more sources

Distributed Model Predictive Consensus of MASs Against False Data Injection Attacks and Denial-of-Service Attacks

IEEE Transactions on Automatic Control
This article provides a secure distributed output feedback model predictive control (DOFMPC) solution for the leader-following consensus problems of homogeneous linear disturbed multi-agent systems against multiple cyber attacks. The false data injection
Zhengcai Li, Yang Shi, Shengyuan Xu, Huiling Xu, Lewei Dong   +4 more
semanticscholar   +1 more source

DAMGAT-Based Interpretable Detection of False Data Injection Attacks in Smart Grids

IEEE Transactions on Smart Grid
False data injection attacks (FDIAs) significantly disrupt the secure operation of smart grids by manipulating the measured values collected by intelligent instruments.
Xiangjing Su, Chao Deng, Jiajia Yang, Fengyong Li, Chaojie Li, Yang Fu, Z. Dong   +6 more
semanticscholar   +1 more source