2026-04-30T21:24:25Z https://meral.edu.mm/oai

oai:meral.edu.mm:recid/4658 2021-12-13T02:23:57Z 1582963302567:1597824273898 user-ucsy

Classification of SQL injection, XSS and Path Traversal for Web Application Attack Detection Han, Ei Ei Phyu, Thae Nu Web application attack detection is one of thepopular research areas during these years. SQLinjection, XSS and path traversal attacks are themost commonly occurred types of webapplication attacks. The proposed systemeffectively classifies three attacks by randomforest algorithm to ensure reasonable accuracy.Request length module is computed based on thecertain length of the URL to analyze each recordas normal or attack. Regular pattern analysis isemphasized on the content of URL and otherfeatures to analyze the certain attack patterns.ECML/PKDD standard web attack dataset isused in this system. Combination of randomforest algorithm with request length and regexpattern analysis is proposed to outperform theaccuracy. 2016-02-25 http://hdl.handle.net/20.500.12678/0000004658 https://meral.edu.mm/records/4658