Oppositional Cuckoo Search Based Weighted Fuzzy Rule System in Malicious Web Sites Detection from Suspicious URLs

Abstract

The primary intention of this research is to design malicious web sites detection from Suspicious URLs. Huge web pages are gone by every day over a system and malicious websites may contaminate client machines. In this work, we design the Malicious Web Sites Detection from Suspicious URLs based on Oppositional Cuckoo Search (OCS) algorithm and fuzzy logic classifier (FLC). The system consists of two modules such as (i) feature selection and (ii) classification. At first, we take the four kinds of features from the dataset which have totally thirty features. Among that, we select the important features using OCS algorithm. After that, we train the selected features using FLC and then we calculate the fuzzy score. Finally, in testing, the FLC is detecting the malicious URL based on the fuzzy score. The experimental results demonstrate that the proposed malicious URL detection method outperforms other existing methods.