An Improved Web Fraud Detector And Preventive System With Cortical Algorithm

© 2021 by IJCTT Journal
Volume-69 Issue-10
Year of Publication : 2021
Authors : DR. Laeticiannekaonyejegbu, Bunmi Deborah Millennial-Oriagbo
DOI :  10.14445/22312803/IJCTT-V69I10P108

How to Cite?

DR. Laeticiannekaonyejegbu, Bunmi Deborah Millennial-Oriagbo, "An Improved Web Fraud Detector And Preventive System With Cortical Algorithm," International Journal of Computer Trends and Technology, vol. 69, no. 10, pp. 47-51, 2021. Crossref,

Web fraud contents prevention and detection is now an important topic in the discipline of information security owing to the powerful emerging techniques often utilized by hackers to compromise a user computer system. Some or few web pages are benign midst the majority of web pages contain malicious web content. Most anti-virus packages in use are based on the use of signature-based access, and these are not able to reveal camouflaged malicious HTML codes. Hence, this project work proposed a malicious web page detective and preventive measure using the cortical algorithm approach of machine learning. This project examines the behavior of malicious web pages, compares the existing Naïve Bayes algorithm used in the detection of malicious web content with the proposed Cortical algorithm used for the design and implementation of this new system. Experimental results reveal that the new system is not just capable of detecting the malicious web content on webpages perfectly; it’s also capable of removing iFrames and blocking Popups meant to cause distractions and to frustrate the user`s efforts while working on the computer system. This research is the first of its kind to effectively block Popups and remove iFrames with the use of CORTICAL ALGORITHM.

Web Fraud Detector, Cortical.


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