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Monitoring Insider Attack in Database Systems Using Multiple-Criteria Query Statement Probabilities
Sky Cheolmin Moon,Sam Chung,Barbara Endicott-Popovsky 한국엔터프라이즈아키텍처학회 2015 정보기술아키텍처연구 Vol.12 No.3
Any malicious attack on the database systems performed by an entrusted group of peoplehaving authorized access is called database insider attack. Even though the insider attack has beenlively researched, it is still far from the practical application. We propose a new approach to improvethe limitations in the previous researches. This approach has four objectives: (1) Multi-PreprocessingAlgorithms to observe a query in multiple perspectives (2) Query Probabilities Based Database InsiderMonitoring Methodology based upon Markov Mathematical Model to record insider’s behavioralpatterns with query and query transition probabilities (3) Query Probabilities Time Series Graph tocreate metrics to monitor the insider’s behavior in order to predict insider attack, and (4) Multi-CriteriaQuery Probabilities Based Insider Attack Monitoring System containing the (1)–(3). The results fromthe evaluation show that the proposed system overcomes the limitations and is also capable to monitorinsider’s behavioral data while the database is being updated.