Intrusion Detection Based On Fuzzy Logic Approach Using Simplified Swarm Optimization

-The intrusion is becoming more essential for effective defense against attacks that are constantly changing in magnitude and complexity. Mainly intrusion detection relies on the extensive knowledge of security experts. The paper proposed a new detection mechanism as Fuzzy Intrusion Detection Engine (FIDE) that uses fuzzy logic to access network data. FIDE uses fuzzy analyzer engine to evaluate inputs and generate alerts for security administrators. The FIDE act as a fuzzy classifier, whose knowledge base is act as fuzzy “if-then” rule. This paper describes the components of FIDE architecture, and explains the benefit of fuzzy rule that improve fuzzy sets. Finally, in order to obtain the best result Simplified Swarm Optimization is used to optimize the structure of FIDE. The simulation of the proposed system is trained and tested with actual real time network data. The FIDE IDS can detect a wide range of common attack types. The proposed system shows high accuracy in identifying attacks.