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Prevention of Zero Day Vulnerability in Network Using Ensemble Fuzzy Association and Cuttle Fish Detection
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The data communication between different parts of the universe is managed by the computer networks and the Enterprise Information System (EIS) which rely on them. The privacy and security are the most important factor to be maintained in any network systems. This paper deals about the detection of intrusion attack in the eclipse database using Ensemble fuzzy association (EFA) and Cuttle Fish Algorithm (CFA. The proposed methodology creates a rule-based ensemble model for network diversity metric modeling for the efficient detection of zeroday attacks and to reduce the time consumption. The simulation result shows that the EFA and CFA having efficient detection rates as compared to the existing systems.
Keywords
Enterprise Information System (EIS), Ensemble Fuzzy Association (EFA), Cuttle Fish Algorithm (CFA).
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