Skip to main content

A Synergy between Static and Dynamic Analysis for the Detection of Software Security Vulnerabilities

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5871))

Abstract

The main contribution of this paper is a framework for security testing. The key components of this framework are twofold: First, a static analyzer that automatically identifies suspicious sites of security vulnerabilities in a control flow graph. Second, a test-data generator. The intent is to attempt proving/disproving whether, or not, the suspicious sites are actual vulnerabilities. The paper introduces the static-dynamic hybrid vulnerability detection system, a system that targets the automation of security vulnerability detection in software. The system combines the detection powers of both static and dynamic analysis. Various components compose this model, namely Static Vulnerability Revealer, Goal-Path-oriented System, and Dynamic Vulnerability Detector.

This research is the result of a fruitful collaboration between CSL (Computer Security Laboratory) of Concordia University, DRDC (Defence Research and Development Canada) Valcartier and Bell Canada under the NSERC DND Research Partnership Program.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Build Security (access on April 29, 2009), https://buildsecurityin.us-cert.gov/daisy/bsi/home.html/

  2. Securityfocus (access on February 26, 2009), http://www.securityfocus.com/bid/27796

  3. Bird, D., Munoz, C.: Automatic generation of random self-checking test cases. IBM Systems J. 22(3), 229–245 (1982)

    Article  Google Scholar 

  4. Boyer, R., Elspas, B., Levitt, K.: Select - a formal system for testing and debugging programs by symbolic execution. SIGPLAN Notices 10(6), 234–245 (1975)

    Article  Google Scholar 

  5. Cadar, C., Engler, D.: Execution generated test cases: How to make systems code crash itself (March 2005)

    Google Scholar 

  6. Chakraborty, M., Chakraborty, U.: An analysis of linear ranking and binary tournament selection in genetic algorithms. In: International Conference on Information, Communications and Signal Processing. ICICS (September 1997)

    Google Scholar 

  7. Cigital and National Science Foundation. Genetic algorithms for software test data generation

    Google Scholar 

  8. Clarke, L.: A system to generate test data and symbolically execute programs. IEEE Transactions on Software Engineering 2(3), 215–222 (1976)

    Article  Google Scholar 

  9. Ferguson, R., Korel, B.: The chaining approach for software test data generation. ACM Transaction on Software Engineering and Methodology 5, 63–86 (1996)

    Article  Google Scholar 

  10. Godefroid, P., Klarlund, N., Sen, K.: Dart: Directed automated random testing (June 2005)

    Google Scholar 

  11. Hadjidj, R., Yang, X., Tlili, S., Debbabi, M.: Model-checking for software vulnerabilities detection with multi-language support (October 2008)

    Google Scholar 

  12. Kiefer, S., Schwoon, S., Suwimonteerabuth, D.: Moped - a model-checker for pushdown systems, http://www.fmi.uni-stuttgart.de/szs/tools/moped/

  13. Korel, B.: Automated software test data generation. IEEE Transactions on Software Enfineering 16(8) (August 1990)

    Google Scholar 

  14. Ligatti, J., Bauer, L., Walker, D.: Enforcing non-safety security policies with program monitors (January 2005)

    Google Scholar 

  15. Novillo, D.: Tree ssa: A new optimization infrastructure for gcc. In: Proceedings of the GCC Developers Summit3, pp. 181–193 (2003)

    Google Scholar 

  16. GNU Project. GCC, the GNU Compiler Collection, http://gcc.gnu.org/

  17. Schneider, F.B.: Enforceable security policies. ACM Transaction of Information System Security (2000)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Hanna, A., Ling, H.Z., Yang, X., Debbabi, M. (2009). A Synergy between Static and Dynamic Analysis for the Detection of Software Security Vulnerabilities. In: Meersman, R., Dillon, T., Herrero, P. (eds) On the Move to Meaningful Internet Systems: OTM 2009. OTM 2009. Lecture Notes in Computer Science, vol 5871. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-05151-7_5

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-05151-7_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-05150-0

  • Online ISBN: 978-3-642-05151-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics