FDIPP: False Data Injection Prevention Protocol for Smart Grid Distribution Systems
نویسندگان
چکیده
منابع مشابه
False Data Injection Attacks in Smart Grid: Challenges and Solutions
Smart Grid, as an energy-based Cyber-Physical Sys tem (CPS), is a new type of power grid that will provide reliable, secure, and efficient energy transmission and distribution. As the quality of assurance of monitoring data is essential to smart grid, in this talk we will first present two dangerous false data injection attacks, which target the state estimation and energy distribution in smar...
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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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In recent years, Information Security has become a notable issue in the energy sector. After the invention of ‘The Stuxnet worm’ [1] in 2010, data integrity, privacy and confidentiality has received significant importance in the real-time operation of the control centres. New methods and frameworks are being developed to protect the National Critical Infrastructures likeenergy sector. In the re...
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In today's Smart Grid, the power Distribution System Operator (DSO) uses real-time measurement data from the Advanced Metering Infrastructure (AMI) for efficient, accurate and advanced monitoring and control. Smart Grids are vulnerable to sophisticated data integrity attacks like the False Data Injection (FDI) attack on the AMI sensors that produce misleading operational decision of the power s...
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Existing prevention-based secure in-network data aggregation schemes for the smart grids cannot effectively detect accidental errors and falsified data injected by malfunctioning or compromised meters. In this work, we develop a light-weight anomaly detector based on kernel density estimator to locate the smart meter from which the falsified data is injected. To reduce the overhead at the colle...
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ژورنال
عنوان ژورنال: Sensors
سال: 2020
ISSN: 1424-8220
DOI: 10.3390/s20030679