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- W4285156760 abstract "In a cyber-physical system, there is an exponential rise in cyber-attacks targeting power grid monitoring systems. False data injection attacks (FDIAs) are potential threats to the security of the smart grid as they can bypass the bad data detection (BDD) attack by manipulation of the power system state estimation (SE). Most works on false data injection (FDI) attack detection comprise computationally expensive and memory-intensive models to detect and analyze the attack. This paper introduces a cost-effective iterative procedure that conducts the load flow analysis using the efficient and improved Newton–Raphson (N-R) method. The aim is to detect the attacked node by comparing bus states’ comparison analysis before and after the attack. It is implemented by creating instances of false data injection. Further, we discuss a defense mechanism to avoid such attacks in the future. Case studies on the IEEE-9, 14, 30, 57, and 118- bus systems demonstrate that the proposed method can inject and detect the FDI attack on different voltage magnitudes." @default.
- W4285156760 created "2022-07-14" @default.
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- W4285156760 date "2022-01-01" @default.
- W4285156760 modified "2023-10-18" @default.
- W4285156760 title "False Data Injection and Detection in Smart Grid Cyber-Physical Systems by Iterative Load Flow Analysis" @default.
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- W4285156760 doi "https://doi.org/10.1007/978-981-19-0619-0_22" @default.
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