A Lightweight Abnormality Detection Mechanism by Stray Packets Analysis

Yong Jin, Satoshi Matsuura, Takao Kondo, Tatsumi Hosokawa, Masahiko Tomoishi

研究成果: Conference contribution


An academic organization network, e.g., a campus network, is running with limited financial support and manpower while it faces the same operational issues and cybersecurity threats as other organizations. Including the existing network facilities and computers for service providing, the increase of mobile devices such as BYOD becomes an issue in terms of misconfiguration and vulnerabilities. The current security systems focus on the backbone network so that the detailed traffic monitoring and data analysis cannot cover the abnormal behavior of all individual endpoints. In general, a misconfigured or intruded computer conducts some abnormal behavior, e.g., sending stray packets, compared to a normal device. Based on this point, we propose a lightweight abnormality detection mechanism by monitoring the stray packets in order to mitigate the above issues. As a result, not only the abnormal behavior can be detected but also maintain the performance of the existing security systems. In this paper, we describe the design and architecture of our proposed Traffic Analyzer', including the implementation and evaluation of our prototype system.

ホスト出版物のタイトルSIGUCCS 2023 - Proceedings of the 2023 ACM SIGUCCS Annual Conference
出版社Association for Computing Machinery
出版ステータスPublished - 2023 3月 20
イベント50th ACM SIGUCCS User Services Annual Conference, SIGUCCS 2023 - Chicago, United States
継続期間: 2023 3月 262023 3月 29


名前Proceedings ACM SIGUCCS User Services Conference


Conference50th ACM SIGUCCS User Services Annual Conference, SIGUCCS 2023
国/地域United States

ASJC Scopus subject areas

  • コンピュータ サイエンスの応用
  • ソフトウェア
  • 情報システム
  • 教育


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