Quantitative Security Evaluation for Software System from Vulnerability Database

Abstract

This paper proposes a quantitative security evaluation for software system from the vulnerability data consisting of discovery date, solution date and exploit publish date based on a stochastic model. More precisely, our model considers a vulnerability life-cycle model and represents the vulnerability discovery process as a non-homogeneous Poisson process. In a numerical example, we show the quantitative measures for contents management system of an open source project.

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H. Okamura, M. Tokuzane and T. Dohi, "Quantitative Security Evaluation for Software System from Vulnerability Database," Journal of Software Engineering and Applications, Vol. 6 No. 4A, 2013, pp. 15-23. doi: 10.4236/jsea.2013.64A003.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] E. M. Clarke Jr., O. Grumberg and D. A. Peled, “Model Checking,” MIT Press, Cambridge, 1999.
[2] G. J. Myers and C. Sandler, “The Art of Software Testing,” John Wiley & Sons, Hoboken, 2004.
[3] H. Okamura, M. Tokuzane and T. Dohi, “Optimal Security Patch Release Timing under Non-Homogeneous Vulnerability-Discovery Processes,” Proceedings of 20th International Symposium on Software Reliability Engineering (ISSRE’09), Mysuru, 16-19 November 2009, pp. 120-128.
[4] H. Okamura, M. Tokuzane and T. Dohi, “Security Evaluation for Software System with Vulnerability Life Cycleand User Profiles,” Proceedings of 2012 Workshop on Dependable Transportation/Recent Advances in Software Dependability (WDTS-RASD 2012), Niigata, 18-19 No-vember 2012, pp. 39-44.
[5] H. Wang and P. Liu, “Modeling and Evaluating the Survivability of an Intrusion Tolerant Database System,” ESORICS 2006, LNCS 4189, Hamburg, 18-20 September 2006, pp. 207-224.
[6] E. Jonsson and T. Olovsson, “A Quantitative Model of the Security Intrusion Process Based Onattacker Behavior,” IEEE Transactions on Software Engineering, Vol. 23, No. 4, 1997, pp. 235-245. doi:10.1109/32.588541
[7] M. Kimura, “A Study on Software Vulnerability Assessment Modeling and Its Application to E-Mail Distribution Software System,” The Journal of Reliability Engineering Association of Japan (Japanese), Vol. 25, No. 3, 2003, pp. 279-283.
[8] T. Fujiwara and S. Yamada, “Testing-Domain Dependent Software Reliability Growth Models and Their Comparisons of Goodness-of-Fit,” Proceedings of the 7th ISSAT International Conference on Reliability and Quality in Design, Washington DC, 8-10 August 2001, pp. 36-40.
[9] W. A. Arbaugh, W. L. Fithen and J. McHugh “`Windows of Vulnerability: A Case Study Analysis,” IEEE Computer, Vol. 33, No. 12, 2000, pp. 52-59. doi:10.1109/2.889093
[10] J. D. Musa, “Software Reliability Engineering,” McGrawHill, New York, 1999.
[11] M. R. Lyu, “Handbook of Software Reliability Engineering,” McGraw-Hill, New York, 1996.
[12] M. Ohba, “Inflection S-Shaped Software Reliability Growth Model,” In: S. Osaki and Y. Hatoyama, Eds., Stochastic Models in Reliability Theory, Springer-Varlag, Berlin, 1984, pp. 144-165. doi:10.1007/978- 3-642-45587-2_10
[13] H. Okamura, T. Dohi and S. Osaki, “EM Algorithms for Logistic Software Reliability Models,” Proceedings of 7th IASTED International Conference on Software Engineering, Innsbruck, 17-19 February 2004, pp. 14-22.
[14] O. H. Alhazmi and Y. K. Malaiya, “Application of Vulnerability Discovery Models to Major Operating Systems,” IEEE Transactions on Reliability, Vol. 57, No. 1, 2008, pp. 14-22. doi:10.1109/TR. 2008.916872
[15] O. H. Alhazmi and Y. K. Malaiya, “Measuring and Enhancing Prediction Capabilities of Vulnerability Discovery Models for Apache and IIS HTTP Servers,” Proceedings of 17th International Symposium on Software Reliability Engineering, Raleigh, 7-10 November 2006, pp. 343-352.
[16] S.-W. Woo, O. H. Alhazmi and Y. K. Malaiya, “Assessing Vulnerabilities in Apache and IIS HTTP Servers,” Proceedings of 2nd IEEE International Symposium on Dependable, Autonomic and Secure Computing, Indianapolis, 29 September-1 October 2006, pp. 103-110.
[17] O. H. Alhazmi and Y. K. Malaiya, “Modeling the Vulnerability Discovery Process,” Proceedings of 16th International Symposium on Software Reliability Engineering, Chicago, 8-11 November 2005, pp. 129-138.
[18] H. Tijms, “A First Course in Stochastic Models,” John Wiley & Sons, Hoboken, 2003. doi:10.1002/047 001363X
[19] H. Okamura, Y. Watanabe and T. Dohi, “An Iterative Scheme for Maximum Likelihood Estimation in Software Reliability Modeling,” Proceedings of 14th International Symposium on Software Reliability Engineering, Denver, 17-20 November 2003, pp. 246-256.
[20] H. Okamura, A. Murayama and T. Dohi, “EM Algorithm for Discrete Software Reliability Models: A Unified Parameter Estimation Method,” Proceedings of 8th IEEE International Symposium on High Assurance Systems Engineering, Tampa, 25-26 March 2004, pp. 219-228.
[21] K. Ohishi, H. Okamura and T. Dohi, “Gompertz Software Reliability Model: Estimation Algorithm and Empirical Validation,” Journal of Systems and Software, Vol. 82, No. 3, 2009, pp. 535-543. doi:10.1016/j.jss.2008.11.840
[22] H. Akaike, “Information Theory and an Extension of the Maximum Likelihood Principle,” Proceedings of 2nd International Symposium on Information Theory, 1973, pp. 267-281.
[23] A. L. Goel and K. Okumoto, “Time-Dependent ErrorDetection Rate Model for Software Reliability and Other Performance Measures,” IEEE Transactions on Reliability, Vol. R-28, No. 3, 1979, pp. 206-211. doi:10.1109/TR.1979.5220566
[24] S. Yamada, M. Ohba and S. Osaki, “S-Shaped Reliability Growth Modeling for Software Error Detection,” IEEE Transactions on Reliability, Vol. R-32, No. 5, 1983, pp. 475-478. doi:10.1109/TR. 1983.5221735
[25] B. Littlewood, “Rationale for a Modified Duane Model,” IEEE Transactions on Reliability, Vol. R-33, No. 2, 1984, pp. 157-159. doi:10.1109/TR.1984.5221762
[26] H. Okamura, Y. Watanabe and T. Dohi, “Estimating Mixed Software Reliability Models Based on the EM Algorithms,” Proceedings of 2002 International Symposium on Empirical Software Engineering, Napa, 3-4 October 2002, pp. 69-78.
[27] H. Okamura, T. Dohi and S. Osaki, “Software Reliability Growth Models with Normal Failure Time Distributions,” Reliability Engineering and System Safety, 2013 (in Press).
[28] J. A. Achcar, D. K. Dey and M. Niverthi, “A Bayesian Approach Using Nonhomogeneous Poisson Processes for Software Reliability Models,” In: A. P. Basu, K. S. Basu and S. Mukhopadhyay, Eds., Frontiers in Reliability, World Scientific, Singapore City, 1998, pp. 1-18.
[29] S. S. Gokhale and K. S. Trivedi, “Log-Logistic Software Reliability Growth Model,” Proceedings of 3rd IEEE International High-Assurance Systems Engineering Symposium, Washington DC, 13-14 November 1998, pp. 34-41.
[30] A. L. Goel, “Software Reliability Models: Assumptions, Limitations and Applicability,” IEEE Transactions on Software Engineering, Vol. SE-11, No. 12, 1985, pp. 1411-1423. doi:10.1109/TSE.1985.232177
[31] H. Okamura, T. Dohi and K. S. Trivedi, “A Refined EM Algorithm for PH Distributions,” Performance Evaluation, Vol. 68, No. 10, 2011, pp. 938-954. doi:10.1016/j.peva.2011.04.001
[32] Q.-M. He and H. Zhang, “On Matrix Exponential Distributions,” Advances in Applied Probability, Vol. 39, No. 1, 2007, pp. 271-292. doi:10.1239/aap/1175266478

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