Rule-based database intrusion detection using coactive artificial neuro-fuzzy inference system and genetic algorithm
by Anitarani Brahma; Suvasini Panigrahi; Neelamani Samal; Debasis Gountia
International Journal of Business Intelligence and Data Mining (IJBIDM), Vol. 21, No. 1, 2022

Abstract: Recently, a fuzzy system having learning and adaptation capabilities is gaining lots of interest in research communities. In the current approach, two of the most successful soft computing approaches - neural network and genetic algorithm with learning capabilities are hybridised to approximate reasoning method of fuzzy systems. The objective of this paper is to develop a coactive neuro-fuzzy inference system with genetic algorithm-based database intrusion detection system that can detect malicious transactions in database very efficiently. Experimental investigation and comparative assessment has been conducted with an existing statistical database intrusion technique to justify the efficacy of the proposed system.

Online publication date: Mon, 04-Jul-2022

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