A XSS Attack Detection Method Based on Subsequence Matching Algorithm

Autor:	Zhang Jingyu, Huo Shumin, Li Huanruo, Hu Hongchao
Rok vydání:	2021
Předmět:	Computer science business.industry Cross-site scripting computer.software_genre Internet security Substring Set (abstract data type) Key point Subsequence Limit (mathematics) Data mining business computer Blossom algorithm
Zdroj:	2021 IEEE International Conference on Artificial Intelligence and Industrial Design (AIID).
DOI:	10.1109/aiid51893.2021.9456515
Popis:	XSS vulnerabilities are one of the main threats to current Web security, and measures must be taken to reduce the growing threat of XSS attacks. This research proposes a detection technique using a subsequence matching algorithm. The key point of the matching algorithm during detection is to find the common subsequence of the input parameters and the generated data, and set a threshold to limit the length of the common substring. The results obtained show that the proposed technique can successfully detect XSS vulnerabilities. Therefore, the technology proved to be more effective in detecting XSS attacks.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::6ed8f0b8da428027e579d7a60d1c1d19 https://doi.org/10.1109/aiid51893.2021.9456515 Zobrazit plný text záznamu