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Detecting recurring and similar software vulnerabilities

Published:01 May 2010Publication History

ABSTRACT

New software security vulnerabilities are discovered on almost daily basis and it is vital to be able to identify and resolve them as early as possible. Fortunately, many software vulnerabilities are recurring or very similar, thus, one could effectively detect and fix a vulnerability in a system by consulting the similar vulnerabilities and fixes from other systems. In this paper, we propose, SecureSync, an automatic approach to detect and provide suggested resolutions for recurring software vulnerabilities on multiple systems sharing/using similar code or API libraries. The core of SecureSync includes a usage model and a mapping algorithm for matching vulnerable code across different systems, a model for the comparison of vulnerability reports, and a tracing technique from a report to corresponding source code. Our preliminary evaluation with case studies showed the potential usefulness of SecureSync.

References

  1. ASF project security information. http://www.apache.org/security/projects.html.Google ScholarGoogle Scholar
  2. Common Vulnerabilities and Exposures (CVE). http://cve.mitre.org/.Google ScholarGoogle Scholar
  3. US-CERT bulletins. http://www.us-cert.gov/.Google ScholarGoogle Scholar
  4. Mozilla.org - Home of the Mozilla Project. www.mozilla.org/.Google ScholarGoogle Scholar
  5. H. A. Nguyen, T. T. Nguyen, N. H. Pham, J. M. Al-Kofahi, and T. N. Nguyen. Accurate and Efficient Structural Characteristic Feature Extraction Method for Clone Detection. In FASE'09. Springer-Verlag. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. T. T. Nguyen, H. A. Nguyen, N. H. Pham, J. M. Al-Kofahi, and T. N. Nguyen. Graph-based Mining of Multiple Object Usage Patterns. In ESEC/FSE 2009. ACM Press, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. J. A. Wang and M. Guo. OVM: an ontology for vulnerability management. In CSIIRW '09: 5th Annual Workshop on Cyber Security and Information Intelligence Research, pages 1--4. ACM Press, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. H. Jiang, T. N. Nguyen, I.-X. Chen, H. Jaygarl, and C. K. Chang. Incremental Latent Semantic Indexing for Automatic Traceability Link Evolution Management. In ASE 2008. IEEE CS Press, 2008.Google ScholarGoogle Scholar

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  1. Detecting recurring and similar software vulnerabilities

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      • Published in

        cover image ACM Conferences
        ICSE '10: Proceedings of the 32nd ACM/IEEE International Conference on Software Engineering - Volume 2
        May 2010
        554 pages
        ISBN:9781605587196
        DOI:10.1145/1810295

        Copyright © 2010 ACM

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 1 May 2010

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