کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4943123 1437622 2017 20 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A statistical unsupervised method against false data injection attacks: A visualization-based approach
ترجمه فارسی عنوان
یک روش آماری ناخواسته در برابر حملات تزریق داده کاذب: رویکرد مبتنی بر تجسم
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی
The proposed method is tested on both the IEEE 14-bus and IEEE 9-bus systems using real load data from the New York independent system operator with the following attack scenarios: (1) attacks without any topology change, (2) attacks after a contingency, and (3) attacks after integration of distributed generations. Experimental results show that our proposed method is superior to the state-of-the-art classification algorithms in dealing with changes. In addition, the reduced data which is helpful in distinguishing between attack and normal patterns can be fed into an expert system for further improvement of the security of the power grid.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 84, 30 October 2017, Pages 242-261
نویسندگان
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