Detection of Web Application Vulnerabilities Accelerated by GPU

DOI

10.2991/mmme-16.2016.188How to use a DOI?

Keywords

XSS, SQLI, Dependence Tree, Automaton, GPU

Abstract

The number and importance of web application increases fast. At the same time, the influence of vulnerabilities in web application grows as well. Automated tools are urgently needed because manual code reviews are inefficient and fallible. However, the time complexity of previous static code detection tools are O(n), which is not acceptable when processing a large quantity of web applications. We propose a novel method based on GPU to accelerate the detection of Web application vulnerabilities. More specifically, we decrease the time complexity of detecting XSS vulnerabilities based on dependence tree from O(n) to O(log(n)) and decrease the time complexity of detecting SQLI vulnerabilities based on automaton from O(n) to O(1). Experiment results show that the method based on GPU is much faster than traditional method based on CPU.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Shaotao Li
PY  - 2016/10
DA  - 2016/10
TI  - Detection of Web Application Vulnerabilities Accelerated by GPU
BT  - Proceedings of the 2016 4th International Conference on Mechanical Materials and Manufacturing Engineering
PB  - Atlantis Press
SP  - 790
EP  - 792
SN  - 2352-5401
UR  - https://doi.org/10.2991/mmme-16.2016.188
DO  - 10.2991/mmme-16.2016.188
ID  - Li2016/10
ER  -