Web Application Attack Detection using Deep Learning
Published in arXiv (Cornell University) • Nov 6, 2020
NobleIDNI4P99W96R45S53
Authors:,
Tikam Alma
Manik Lal Das
Abstract
Modern web applications are dominated by HTTP/HTTPS messages that consist of one or more headers, where most of the exploits and payloads can be injected by attackers. According to the OWASP, the 80 percent of the web attacks are done through HTTP/HTTPS requests queries. In this paper, we present a ...
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