Titlebook: Detection of False Data Injection Attacks in Smart Grid Cyber-Physical Systems; Beibei Li,Rongxing Lu,Gaoxi Xiao Book 2020 The Editor(s) (

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https://doi.org/10.1007/978-3-658-15122-5bad data detection, as well as FmDI attacks against state estimation. In addition, the state-of-the-art literature reviews on existing intrusion detection systems (IDSs), FDI attacks detection, and insider threats detection will also be provided.

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https://doi.org/10.1007/978-3-658-15122-5smission, distribution, and consumption is of prime concern in the twenty-first century. Unfortunately, the massive blackout in northeastern North America in 2003 uncovered the ease with which the electric grids could be taken down. It is, indeed, not the end of the story for the security and reliab

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https://doi.org/10.1007/978-3-658-15122-5bad data detection, as well as FmDI attacks against state estimation. In addition, the state-of-the-art literature reviews on existing intrusion detection systems (IDSs), FDI attacks detection, and insider threats detection will also be provided.

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Situierung und theoretischer Rahmenvolving network threat environment. The increasing complexity of the grid in the network and physical areas also exacerbates the challenges. In this chapter, we develop an analysis model based on stochastic Petri net (SPN) to evaluate and analyze the reliability of smart grid, especially for topolog

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Flustered

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Hartmut Heuermann,Matthias Kuzinaon smart grids, which we term as the PFDD approach. However, few literature has focused on the systematic analysis of the feasibility and limitations of this approach. To meet this gap, in this chapter we pioneer to investigate the feasibility and limitations by employing PFDD to contain FmDI attack

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https://doi.org/10.1007/978-3-030-58672-0Smart grid security; power system security; cybersecurity; cyber-physical systems; false data injection

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978-3-030-58674-4The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl

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