Journal of Network and Systems Management

, Volume 13, Issue 3, pp 269–291 | Cite as

Design and Analysis of Techniques for Detection of Malicious Activities in Database Systems



Existing host-based Intrusion Detection Systems use the operating system log or the application log to detect misuse or anomaly activities. These methods are not sufficient for detecting intrusion in the database systems. In this paper, we describe a method for detecting malicious activities in a database management system by using data dependency relationships. Typically, before a data item is updated in the database, some other data items are read or written. And after the update, other data items may also be written. These data items read or written in the course of update of a data item construct the read set, prewrite set, and the postwrite set for this data item. The proposed method identifies malicious transactions by comparing these sets with data items read or written in user transactions. We have provided mechanisms for finding data dependency relationships among transactions and use Petri-Nets to model normal data update patterns at user task level. Using this method, we ascertain more hidden anomalies in the database log. Our simulation on synthetic data reveals that the proposed model can achieve desirable performance when both transaction and user task level intrusion detection methods are employed.


Malicious transactions intrusion detection anomaly detection data dependency 


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Copyright information

© Springer Science + Business Media, Inc. 2005

Authors and Affiliations

  1. 1.Computer Science and Computer Engineering DepartmentUniversity of ArkansasFayetteville

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