期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2019
卷号：7
期号：5
页码：2915-2918
DOI：10.15680/IJIRCCE.2019. 0705054
出版社：S&S Publications
摘要：Nowadays, the greatest danger to associations is security that originates from its open Web website and
the Web-based applications found there. Dissimilar to interior just system administrations, for example, databases—
which can be closed from the outside by means of firewalls—an open Web webpage is commonly available to any
individual who needs to see it, making application security an issue. As systems have turned out to be increasingly
secure, vulnerabilities in Web applications have definitely pulled in the consideration of programmers, both criminal
and recreational, who have contrived procedures to misuse these openings. Truth be told, assaults upon the Web
application layer currently surpass those led at the system level and can have results which are similarly as harming.
Thus, under the plan, we proposed Exposing Security Measure for Web Site Vulnerabilities or Web Server Intrusion
with Machine Learning Algorithm utilizing KNN to barge in and get imperative and private data from the site,
information servers, web servers, and web application inclined to assaults and frail to ensure its bare essential to protect
if vulnerabilities exists in your Web Server.
关键词：Machine Learning; Cross Site Scripts; SQL Injections; K;Nearest Neighbour; Web Server Intrusion;
