Research Article
VulAware: Towards Massive-Scale Vulnerability Detection in Cyberspace
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@INPROCEEDINGS{10.1007/978-3-030-00557-3_15, author={Zhiqiang Wang and Pingchuan Ma and Ruming Wang and Shichun Gao and Xuying Zhao and Tao Yang}, title={VulAware: Towards Massive-Scale Vulnerability Detection in Cyberspace}, proceedings={Machine Learning and Intelligent Communications. Third International Conference, MLICOM 2018, Hangzhou, China, July 6-8, 2018, Proceedings}, proceedings_a={MLICOM}, year={2018}, month={10}, keywords={Cyber security Vulnerability detection Network attack Security vulnerability}, doi={10.1007/978-3-030-00557-3_15} }- Zhiqiang Wang
Pingchuan Ma
Ruming Wang
Shichun Gao
Xuying Zhao
Tao Yang
Year: 2018
VulAware: Towards Massive-Scale Vulnerability Detection in Cyberspace
MLICOM
Springer
DOI: 10.1007/978-3-030-00557-3_15
Abstract
Due to the delay of threat warning and vulnerability fixing, the critical servers in cyberspace are under potential threat. With the help of vulnerability detection system, we can reduce risk and manage servers efficiently. To date, substantial related works have been done, combined with unenjoyable performance. To address these issues, we present VulAware, which is a distributed framework for detecting vulnerabilities. It is able to detect remote vulnerabilities automatically. Finally, empirical results show that VulAware significantly outperforms the state-of-the-art methods in both speed and robustness.
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