2024

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Framework for detecting outlier and database intrusions
(Igor Sikorsky Kyiv Polytechnic Institute, 2024) Kolomytsev, Mykhailo V.; Nosok, Svitlana O.
This paper presents a methodology and framework for detecting anomalies in the actions of relational database users, with a focus on insider threats. The architecture of the framework is described, including the choice of parameters for logging user behavior and the justification of the anomaly detection algorithm. An overview of the existing anomaly-detection solutions is provided. The proposed methodology for the functioning of the framework is outlined with recommendations on the choice of algorithm parameters. The analysis of insider actions in databases provides an original approach to anomaly detection and contributes to the field of information security.