Open AccessA Study on XSS Attacks: Intelligent Detection Methods
Author(s) -
V S Stency,
N. Mohanasundaram
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1767/1/012047
Subject(s) - cross site scripting , computer science , scripting language , computer security , web application , world wide web , web application security , web page , web development , operating system
Cross-site scripting is one of the standard web application attacks vulnerable to the application layer. The attacker handles malicious scripting for trusted websites and inject the script. There are numerous types of XSS scripting vulnerable to attack websites incredibly open web applications. The attacker can load or redirect to the malicious webpage. The XSS is susceptible to attack significant websites like medical, e-commerce, banking, etc. The detection and prevention of XSS attacks are still complicated. Plenty of research has been carried out to control the XSS based attack. This paper analyses the XSS attack detection methods by various performance metrics. Numerous works issued in the widespread journals between 2019 and 2020 are reviewed in this paper to accomplish these requirements. The reviewed articles are compared concerning algorithms’ simplicity, the type they belong, and the performance metrics. The work assumed that the movement in the application of elementary methods to detect XSS attacks is better than the recommendations that custom some artificial-intelligence techniques.