更新情報
第13回
核セキュリティにおける内部脅威者検知手法の提案
著者:
出町 和之,Kazuyuki DEMACHI,川崎 祐典,Hironori KAWASAKI,陳 実,Shi CHEN,藤田 智之,Tomoyuki FUJITA,兼本 茂,Shigeru KANEMOTO
発刊日:
公開日:
キーワードタグ:
Convolution neural network Feature extraction Nuclear Security Principal Component Analysis Time-series data analysis
出町 和之,Kazuyuki DEMACHI,川崎 祐典,Hironori KAWASAKI,陳 実,Shi CHEN,藤田 智之,Tomoyuki FUJITA,兼本 茂,Shigeru KANEMOTO
発刊日:
公開日:
キーワードタグ:
Convolution neural network Feature extraction Nuclear Security Principal Component Analysis Time-series data analysis
Sabotage by malicious insider is one of significant and serious threats for nuclear security of nuclear power plants. It is difficult, however, to distinguish abnormal behaviors from normal works such as their daily maintenance activities. In this study, a technique was proposed to subdivide the abnormal behavior due to sabotage by image analysis and then to detect and identify the abnormal behavior in real time. ...
英字タイトル:
Proposal of Insider Detection Method for Nuclear Security
英字タイトル:
Proposal of Insider Detection Method for Nuclear Security