Optimization of COCOMO-II Model Parameters Using Hybrid Algorithm of Cuckoo Search Algorithm and GA

In this paper, we propose a classification model for the detection of phishing domains based on classification rules. We formulate these rules based on the results of the analysis and distribute them into three classifiers: the first is related to domain name features, the second is related to SEO information of the domain, and the third is related to security scans by security vendors. Each classifier feds its results to the main classifier, which then evaluates the received results by its rule. We formulate eleven classification rules, which are distributed as follows: six rules for the first classifier, four rules for the second classifier, and one rule for the third classifier. We retrieved domain names from 222 confirmed phishing URLs, tested them using the suggested model, and obtained a 99.1% accuracy rate.