Prediction and detection of cross scripting attack XSS in web application using intrusion detection system IDS: Novel approach - Koteshwar, Marripelli; Singh, Bipin Bihari Jaya (International Journal of Computer Sciences and Engineering, 2020)
In present-day time, most of the associations are making use of web services for improved services to their clients. With the upturn in count of web users, there is a considerable hike in the web attacks. Study indicates that more than 80% of the web applications are vulnerable to cross-site scripting (XSS) attacks. XSS is one of the fatal attacks & it has been practiced over the maximum number of well-known search engines and social sites. At the same time, there are large number of attacks on web applications that are getting popular among attackers. Attacks like injection vulnerabilities such as SQL Injection, Cross site Scripting, Cross site Request Forgery (CSRF) are very common and threatening to the modern web applications. In this paper, we have considered XSS attacks, its prediction and detection different kind of methods applied to repel these attacks with their corresponding limitations. Additionally, we have discussed the proposed approach for defying XSS attack using intrusion detection system. For using IDS cyber-attacks detection system along with KF(knowledge flow model) model approach for prediction cross scripting attack. Finally, the result of vulnerability scanners are shown and analysed before and after the implementation of known XSS security trials.