ANALYSIS OF MOBILE MALEFIC WEBSITE BY KAYO

Authors

  • Dr.P. Srinivasa Rao*, Kundeti Archana, Ampavathi Anusha & Molkar Rajkumar, Bodduna Srinivas & Neelam Thirumala Rao

Keywords:

Cyber security, machine learning, Web networking

Abstract

With regards to content, construction, and usefulness, portable explicit sites contrast decisively from their work area reciprocals. Hence, it is improbable that ordinary strategies to distinguish fake sites will be successful for these sites. In this review, we construct and set up as a regular occurrence kAYO, a framework for recognizing perilous and great portable sites. This end is reached by kAYO in light of the static components of a page, for example, the amount of iframes and the presence of realized false telephone numbers. We initially show tentatively the requirement for versatile explicit methodologies prior to recognizing various new static properties that firmly correspond with pernicious portable pages. Then, at that point, we accomplish 90% grouping precision utilizing kAYO on a dataset of north of 350,000 known harmless and perilous versatile pages. Moreover, we find, dissect, and report on various sites that Google Safe Browsing and Virus Total neglected to find yet that kAYO did. At last, we use kAYO to make a program module that monitors clients from false portable sites continuously. We then, at that point, offer the principal static investigation strategy for recognizing fake portable site pages.

Published

2022-09-20

How to Cite

Dr.P. Srinivasa Rao*, Kundeti Archana, Ampavathi Anusha & Molkar Rajkumar, Bodduna Srinivas & Neelam Thirumala Rao. (2022). ANALYSIS OF MOBILE MALEFIC WEBSITE BY KAYO. Harbin Gongye Daxue Xuebao/Journal of Harbin Institute of Technology, 54(9), 184–196. Retrieved from http://hebgydxxb.periodicales.com/index.php/JHIT/article/view/1325

Issue

Section

Articles