Visible to the public Improvement in Phishing Websites Detection Using Meta Classifiers

TitleImprovement in Phishing Websites Detection Using Meta Classifiers
Publication TypeConference Paper
Year of Publication2019
AuthorsChandra, Yogesh, Jana, Antoreep
Conference Name2019 6th International Conference on Computing for Sustainable Global Development (INDIACom)
KeywordsAccuracy, Computer crime, ensemble classifiers, F-measure, false trust, fraudulent practices, fraudulent websites, Internet, Internet security, Meta Classifier, meta classifiers, modern computers, pattern classification, personal information, phishing, phishing Websites, Phishing Websites Detection, policy-based governance, Policy-Governed Secure Collaboration, pubcrawl, resilience, Resiliency, Scalability, single classifier model, smart devices, Trusted Computing, trusted Web pages, Web sites, WEKA

In the era of the ever-growing number of smart devices, fraudulent practices through Phishing Websites have become an increasingly severe threat to modern computers and internet security. These websites are designed to steal the personal information from the user and spread over the internet without the knowledge of the user using the system. These websites give a false impression of genuinity to the user by mirroring the real trusted web pages which then leads to the loss of important credentials of the user. So, Detection of such fraudulent websites is an essence and the need of the hour. In this paper, various classifiers have been considered and were found that ensemble classifiers predict to utmost efficiency. The idea behind was whether a combined classifier model performs better than a single classifier model leading to a better efficiency and accuracy. In this paper, for experimentation, three Meta Classifiers, namely, AdaBoostM1, Stacking, and Bagging have been taken into consideration for performance comparison. It is found that Meta Classifier built by combining of simple classifier(s) outperform the simple classifier's performance.

Citation Keychandra_improvement_2019