Results 31 to 40 of about 45,445 (284)

Subspace Methods for Data Attack on State Estimation: A Data Driven Approach [PDF]

, 2014
Data attacks on state estimation modify part of system measurements such that the tempered measurements cause incorrect system state estimates. Attack techniques proposed in the literature often require detailed knowledge of system parameters.
Jinsub Kim, Lang Tong, Life Fellow, Robert J. Thomas   +3 more
core   +1 more source

Location Detection of False Data Injection Attacks in Power Grid Based on Improved Deep Extreme Learning Machine

发电技术
ObjectivesPower systems are facing threats of false data injection attacks. Existing detection methods for false data injection attacks have the problems of insufficient feature learning ability and slow detection speed, making it difficult to locate ...
XI Lei, WANG Yixiao, XIONG Yahui, DONG Lu   +3 more
doaj   +1 more source

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

Modeling and performance evaluation of stealthy false data injection attacks on smart grid in the presence of corrupted measurements

, 2016
The false data injection (FDI) attack cannot be detected by the traditional anomaly detection techniques used in the energy system state estimators. In this paper, we demonstrate how FDI attacks can be constructed blindly, i.e., without system knowledge,
Anwar, Adnan, Mahmood, Abdun Naser, Pickering, Mark   +2 more
core   +1 more source

Detection of False Data Injection Attacks in Smart Grid under Colored Gaussian Noise

, 2016
In this paper, we consider the problems of state estimation and false data injection detection in smart grid when the measurements are corrupted by colored Gaussian noise.
He, Haibo, Kay, Steven, Tang, Bo, Yan, Jun   +3 more
core   +1 more source

Achieving Efficient Detection Against False Data Injection Attacks in Smart Grid

IEEE Access, 2017
Internet of Things (IoT) technologies have been broadly applied in smart grid for monitoring physical or environmental conditions. Especially, state estimation is an important IoT-based application in smart grid, which is used in system monitoring to get
Ruzhi Xu, Rui Wang, Zhitao Guan, Longfei Wu, Jun Wu, Xiaojiang Du   +5 more
doaj   +1 more source

Load frequency control under false data inject attacks based on multi-agent system method in multi-area power systems

International Journal of Distributed Sensor Networks, 2022
This article considers the load frequency control of multi-area power system-based multi-agent system method under false data injection attacks. The research can provide better solutions for multi-area power system load frequency control under false data
Tengfei Weng, Yan Xie, Guorong Chen, Qi Han, Yuan Tian, Liping Feng, Yangjun Pei   +6 more
doaj   +1 more source

Data-driven control against false data injection attacks

Automatica
The rise of cyber-security concerns has brought significant attention to the analysis and design of cyber-physical systems (CPSs). Among the various types of cyberattacks, denial-of-service (DoS) attacks and false data injection (FDI) attacks can be easily launched and have become prominent threats.
Liu, Wenjie, Li, Lidong, Sun, Jian, Deng, Fang, Wang, Gang, Chen, Jie   +5 more
openaire   +3 more sources

Biometric Backdoors: A Poisoning Attack Against Unsupervised Template Updating

, 2020
In this work, we investigate the concept of biometric backdoors: a template poisoning attack on biometric systems that allows adversaries to stealthily and effortlessly impersonate users in the long-term by exploiting the template update procedure.
Eberz, Simon, Lovisotto, Giulio, Martinovic, Ivan   +2 more
core   +1 more source

Energy Market Manipulation via False-Data Injection Attacks: A Review

IEEE Access
Locational Marginal Prices (LMPs) are critical indicators in modern energy markets, representing the cost of delivering electricity at specific locations while considering the generation and transmission constraints.
Ghadeer O. Alsharif, Christos Anagnostopoulos, Angelos K. Marnerides   +2 more
doaj   +1 more source