A Lightweight Abnormality Detection Mechanism by Stray Packets Analysis
SIGUCCS（2023）
Tokyo Institute of Technology
Abstract
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.
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Key words
Anomaly Detection,Deep Packet Inspection,Botnet Detection,Intrusion Detection,Packet Classification
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