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Attack data analysis to find Cross Site Scripting attack patterns

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Title: Attack data analysis to find Cross Site Scripting attack patterns

Authors: Pmd Nagarjun, Shaik Shakeel Ahamad

Journal: ARPN Journal of Engineering and Applied Sciences

HEC Recognition History
Category From To
Y 2023-07-01 2024-09-30
Y 2022-07-01 2023-06-30
Y 2021-07-01 2022-06-30
X 2020-07-01 2021-06-30

Publisher: Khyber Medical College, Peshawar

Country: Pakistan

Year: 2018

Volume: 13

Issue: 17

Language: English

Categories
Computer Science (14978) Network Security (293) Cross-Site Scripting (1) Attack Analysis (1) Web Security (14)

Abstract

Cross Site Scripting (XSS) attacks are most popular web application attacks. In XSS attacks, the attacker injects malicious code into a web application and execution of that malicious code at the browser side may steal session tokens, web cookies, or other sensitive information of the user. In this paper, we analyzed a large collection of XSS attacks to find XSS attack patterns. Based on this analysis, we are able to find XSS attacks effects on different programming languages, domain extensions, and common web pages. Furthermore able to find script tags frequency, keywords frequency, and special characters frequency in XSS attacks. We also reviewed different prevention techniques of XSS attacks.

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