Role-Based Profiling Using Fuzzy Adaptive Resonance Theory for Securing Database Systems

Anitarani Brahma and Suvasini Panigrahi
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Anitarani Brahma: Department of Computer Science and Engineering, Veer Surendra Sai University of Technology, Burla, India
Suvasini Panigrahi: Department of Computer Science and Engineering, Veer Surendra Sai University of Technology, Burla, India

International Journal of Applied Metaheuristic Computing (IJAMC), 2021, vol. 12, issue 2, 36-48

Abstract: Very large amounts of time and effort have been invested by the research community working on database security to achieve high assurance of security and privacy. An important component of a secure database system is intrusion detection system which has the ability to successfully detect anomalous behavior caused by applications and users. However, modeling the normal behavior of a large number of users in a huge organization is quite infeasible and inefficient. The main purpose of this research investigation is thus to model the behavior of roles instead of users by applying adaptive resonance theory neural network. The observed behavior which deviates from any of the established role profiles is treated as malicious. The proposed model has the advantage of identifying insider threat and is applicable for large organizations as it is based on role profiling instead of user profiling. The proposed system is capable of detecting intrusion with high accuracy along with minimized false alarms.

Date: 2021
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