An Advanced Filtering Mechanism for Analysis and Detection of Malicious Web Pages

Abstract

Internet services are more necessary part of our daily life.
We rely growingly on the ease and flexibility of Internet connected
devices to shop, communicate and in general perform tasks that
would require our physical presence. While very valuable, Internet
transactions can represent user sensitive information. Banking
sector’s and personal medical records, system authorization
passwords and personal communication records can easily become
known to an enemy who can easily compromise any of the devices
include in online transactions. Regrettably, In this transaction the
user’s personal computer seems to be the weakest link. At the same
time attacker also use new attacks for identification of user’s
sensitive information with vulnerabilities that use a small part of
code in web pages. Overcome these problems use a novel approach
for a filtering technique to finding malicious web pages very
effectively and efficiently using supervised machine learning. Also
detailed study some other techniques researcher research to analysis
and detection of malicious web pages.