About | Contact Us | Register | Login
ProceedingsSeriesJournalsSearchEAI
2nd International ICST Conference on Communications and Networking in China

Research Article

Using Network Attack Graph to Predict the Future Attacks

Cite
BibTeX Plain Text
  • @INPROCEEDINGS{10.1109/CHINACOM.2007.4469413,
        author={Jie Lei and Zhi-tang Li},
        title={Using Network Attack Graph to Predict the Future Attacks},
        proceedings={2nd International ICST Conference on Communications and Networking in China},
        publisher={IEEE},
        proceedings_a={CHINACOM},
        year={2008},
        month={3},
        keywords={Computer science  Data security  Forensics  Inference mechanisms  Intrusion detection  Libraries  Protection  Real time systems  Testing  Tree graphs},
        doi={10.1109/CHINACOM.2007.4469413}
    }
    
  • Jie Lei
    Zhi-tang Li
    Year: 2008
    Using Network Attack Graph to Predict the Future Attacks
    CHINACOM
    IEEE
    DOI: 10.1109/CHINACOM.2007.4469413
Jie Lei1,*, Zhi-tang Li1,*
  • 1: Computer Science Department Huazhong University of Science and Technology 430074 Wuhan - Hubei - China
*Contact email: leijie@hust.edu.cn, leeying@hust.edu.cn

Abstract

An intrusion detection system (IDS) generates alerts indicating what malicious behaviors are going on against the protected network system. When comparing the real-time reported IDS alerts with the network attack graph which provides all possible sequences of exploits that an intruder may use to penetrate the system, some prediction on future attacks can be made. In this paper we proposed a novel approach to predicting future attacks. First an attack graph is generated through data mining and the predictability of every attack scenario which represents how probable there would be oncoming attacks following the attack scenario can be estimated. Then in real-time intrusion detection environment the IDS alerts are correlated into attack scenarios and ranked by their predictability scores. Finally the attack scenarios with high predictability are used as the evidence to make prediction on future attacks. The effectiveness of the approach has been validated with a honeynet system.

Keywords
Computer science Data security Forensics Inference mechanisms Intrusion detection Libraries Protection Real time systems Testing Tree graphs
Published
2008-03-07
Publisher
IEEE
Modified
2011-07-19
http://dx.doi.org/10.1109/CHINACOM.2007.4469413
Copyright © 2007–2025 IEEE
EBSCOProQuestDBLPDOAJPortico
EAI Logo

About EAI

  • Who We Are
  • Leadership
  • Research Areas
  • Partners
  • Media Center

Community

  • Membership
  • Conference
  • Recognition
  • Sponsor Us

Publish with EAI

  • Publishing
  • Journals
  • Proceedings
  • Books
  • EUDL