Machine Learning and Intelligent Communications. Third International Conference, MLICOM 2018, Hangzhou, China, July 6-8, 2018, Proceedings

Research Article

VulAware: Towards Massive-Scale Vulnerability Detection in Cyberspace

  • @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
Zhiqiang Wang1,*, Pingchuan Ma1,*, Ruming Wang2, Shichun Gao1, Xuying Zhao1, Tao Yang3
  • 1: Beijing Electronic Science and Technology Institute
  • 2: Hainan University
  • 3: Key Lab of Information Network Security of Ministry of Public Security
*Contact email: wangzq@besti.edu.cn, 20162308@mail.besti.edu.cn

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.