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- W2018034384 abstract "Data Warehouse (DW) systems maintain sensitive and crucial information, which is integrated from various heterogenous sources of organization. With the ever increasing deployment and usage of networks, these systems are becoming more vulnerable to malicious attacks. With the increased number of attacks, intrusion detection has become vital part of Information Security. In this paper, we have proposed a model for analyzing and detecting anomalous events based on user behavior analysis through usage patterns, user profiles and session management. After monitoring the events in the system, if any intrusion activity occurs, then alerts are issued to system administrators. Since a user profile is not necessarily fixed but rather it evolves with changing time, so a dynamic user behavior modeling is represented as a sequence of events and combination of fact and dimension tables accessed by the users. In this way, DW systems may be protected by the malicious attacks." @default.
- W2018034384 created "2016-06-24" @default.
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- W2018034384 date "2012-11-27" @default.
- W2018034384 modified "2023-09-27" @default.
- W2018034384 title "A proposed model for data warehouse user behaviour using intrusion detection system" @default.
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- W2018034384 doi "https://doi.org/10.1145/2382756.2382771" @default.
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