False Data Injection Attacks Detection in Power System Using Machine Learning Method
نویسندگان
چکیده
منابع مشابه
Resilient Configuration of Distribution System versus False Data Injection Attacks Against State Estimation
State estimation is used in power systems to estimate grid variables based on meter measurements. Unfortunately, power grids are vulnerable to cyber-attacks. Reducing cyber-attacks against state estimation is necessary to ensure power system safe and reliable operation. False data injection (FDI) is a type of cyber-attack that tampers with measurements. This paper proposes network reconfigurati...
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False data injection (FDI) is considered to be one of the most dangerous cyber-attacks in smart grids, as it may lead to energy theft from end users, false dispatch in the distribution process, and device breakdown during power generation. In this paper, a novel kind of FDI attack, named tolerable false data injection (TFDI), is constructed. Such attacks exploit the traditional detector’s toler...
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False data injection (FDI) attacks are a crucial security threat to smart grid cyber-physical system (CPS), and could result in cataclysmic consequences to the entire power system. However, due to the high dependence on open information networking, countering FDI attacks is challenging in smart grid CPS. Most existing solutions are based on state estimation (SE) at the highly centralized contro...
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ژورنال
عنوان ژورنال: Journal of Computer and Communications
سال: 2018
ISSN: 2327-5219,2327-5227
DOI: 10.4236/jcc.2018.611025