{"title":"Detection of False Data Injection Attacks in Distributed State Estimation of Power Networks","authors":"Sho OBATA, Koichi KOBAYASHI, Yuh YAMASHITA","doi":"10.1587/transfun.2022map0010","DOIUrl":null,"url":null,"abstract":"In a power network, it is important to detect a cyber attack. In this paper, we propose a method for detecting false data injection (FDI) attacks in distributed state estimation. An FDI attack is well known as one of the typical cyber attacks in a power network. As a method of FDI attack detection, we consider calculating the residual (i.e., the difference between the observed and estimated values). In the proposed detection method, the tentative residual (estimated error) in ADMM (Alternating Direction Method of Multipliers), which is one of the powerful methods in distributed optimization, is applied. First, the effect of an FDI attack is analyzed. Next, based on the analysis result, a detection parameter is introduced based on the residual. A detection method using this parameter is then proposed. Finally, the proposed method is demonstrated through a numerical example on the IEEE 14-bus system.","PeriodicalId":55003,"journal":{"name":"Ieice Transactions on Fundamentals of Electronics Communications and Computer Sciences","volume":null,"pages":null},"PeriodicalIF":0.4000,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ieice Transactions on Fundamentals of Electronics Communications and Computer Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1587/transfun.2022map0010","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE","Score":null,"Total":0}
引用次数: 1
Abstract
In a power network, it is important to detect a cyber attack. In this paper, we propose a method for detecting false data injection (FDI) attacks in distributed state estimation. An FDI attack is well known as one of the typical cyber attacks in a power network. As a method of FDI attack detection, we consider calculating the residual (i.e., the difference between the observed and estimated values). In the proposed detection method, the tentative residual (estimated error) in ADMM (Alternating Direction Method of Multipliers), which is one of the powerful methods in distributed optimization, is applied. First, the effect of an FDI attack is analyzed. Next, based on the analysis result, a detection parameter is introduced based on the residual. A detection method using this parameter is then proposed. Finally, the proposed method is demonstrated through a numerical example on the IEEE 14-bus system.
期刊介绍:
Includes reports on research, developments, and examinations performed by the Society''s members for the specific fields shown in the category list such as detailed below, the contents of which may advance the development of science and industry:
(1) Reports on new theories, experiments with new contents, or extensions of and supplements to conventional theories and experiments.
(2) Reports on development of measurement technology and various applied technologies.
(3) Reports on the planning, design, manufacture, testing, or operation of facilities, machinery, parts, materials, etc.
(4) Presentation of new methods, suggestion of new angles, ideas, systematization, software, or any new facts regarding the above.