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Medientyp:
E-Artikel
Titel:
A Study on XSS Attacks: Intelligent Detection Methods
Beteiligte:
Stency, V S;
Mohanasundaram, N
Erschienen:
IOP Publishing, 2021
Erschienen in:
Journal of Physics: Conference Series, 1767 (2021) 1, Seite 012047
Sprache:
Nicht zu entscheiden
DOI:
10.1088/1742-6596/1767/1/012047
ISSN:
1742-6588;
1742-6596
Entstehung:
Anmerkungen:
Beschreibung:
Abstract 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.