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Quantitative Analysis of Attack Defense Trees

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Performance Evaluation Methodologies and Tools (VALUETOOLS 2021)

Abstract

The quantitative analysis of Attack Tree models brings insights on the underlying security-critical systems. Having information on temporal behaviours of such systems lets us check whether at a given time, the probability that the system is compromised is less than a critical threshold or not. Moreover the evaluation of the countermeasure efficiency and the determination of eventual reinforcements of security-critical systems are very important. In this paper, we extend the approach proposed in [11] for numerical analysis of the Attack Tree models to the Attack Defense Tree analysis. The completion times of attacks and countermeasures are defined by finite discrete random variables. The output distribution of the root of an Attack Defense Tree is computed by a bottom-up approach. However the size of the output distribution can become quickly very large. We prove that the method which consists in deriving bounding distributions of reduced sizes by means of the stochastic comparison method can be used in the presence of counter-measure gates.

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References

  1. Aït-Salaht, F., Castel-Taleb, H., Fourneau, J.-M., Pekergin, N.: Stochastic bounds and histograms for network performance analysis. In: Balsamo, M.S., Knottenbelt, W.J., Marin, A. (eds.) EPEW 2013. LNCS, vol. 8168, pp. 13–27. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-40725-3_3

    Chapter  Google Scholar 

  2. Arnold, F., Hermanns, H., Pulungan, R., Stoelinga, M.: Time-dependent analysis of attacks. In: Abadi, M., Kremer, S. (eds.) POST 2014. LNCS, vol. 8414, pp. 285–305. Springer, Heidelberg (2014). https://doi.org/10.1007/978-3-642-54792-8_16

    Chapter  Google Scholar 

  3. Aslanyan, Z., Nielson, F., Parker, D.: Quantitative verification and synthesis of attack-defence scenarios. In: IEEE CSF 2016, pp. 105–119 (2016)

    Google Scholar 

  4. Fourneau, J.M., Pekergin, N.: A numerical analysis of dynamic fault trees based on stochastic bounds. In: Campos, J., Haverkort, B.R. (eds.) QEST 2015. LNCS, vol. 9259, pp. 176–191. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-22264-6_12

    Chapter  Google Scholar 

  5. Gadyatskaya, O., Hansen, R.R., Larsen, K.G., Legay, A., Olesen, M.C., Poulsen, D.B.: Modelling attack-defense trees using timed automata. In: Fränzle, M., Markey, N. (eds.) FORMATS 2016. LNCS, vol. 9884, pp. 35–50. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-44878-7_3

    Chapter  MATH  Google Scholar 

  6. Jhawar, R., Lounis, K., Mauw, S.: A stochastic framework for quantitative analysis of attack-defense trees. In: Barthe, G., Markatos, E., Samarati, P. (eds.) STM 2016. LNCS, vol. 9871, pp. 138–153. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-46598-2_10

    Chapter  Google Scholar 

  7. Kordy, B., Mauw, S., Radomirovic, S., Schweitzer, P.: Attack-defense trees. J. Log. Comput. 24(1), 55–87 (2014)

    Article  MathSciNet  Google Scholar 

  8. Kordy, B., Piètre-Cambacédès, L., Schweitzer, P.: Dag-based attack and defense modeling: Don’t miss the forest for the attack trees. Comput. Sci. Rev. 13–14, 1–38 (2014)

    Article  Google Scholar 

  9. Kumar, R., Ruijters, E., Stoelinga, M.: Quantitative attack tree analysis via priced timed automata. In: Sankaranarayanan, S., Vicario, E. (eds.) FORMATS 2015. LNCS, vol. 9268, pp. 156–171. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-22975-1_11

    Chapter  MATH  Google Scholar 

  10. Kumar, R., Stoelinga, M.: Quantitative security and safety analysis with attack-fault trees. In: HASE 2017, pp. 25–32 (2017)

    Google Scholar 

  11. Pekergin, N., Tan, S., Fourneau, J.-M.: Quantitative attack tree analysis: stochastic bounds and numerical analysis. In: Kordy, B., Ekstedt, M., Kim, D.S. (eds.) GraMSec 2016. LNCS, vol. 9987, pp. 119–133. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-46263-9_8

    Chapter  Google Scholar 

  12. Petrucci, L., Knapik, M., Penczek, W., Sidoruk, T.: Squeezing state spaces of (attack-defence) trees. In: Pang, J., Sun, J. (eds.) ICECCS 2019, pp. 71–80 (2019)

    Google Scholar 

  13. Roy, A., Seong, D., Kim, K.T.: Act:towards unifying the constructs of attack and defense trees. Securtiy Commun. Netw. 3, 1–15 (2011)

    Article  Google Scholar 

  14. Ruijters, E., Stoelinga, M.: Fault tree analysis: a survey of the state-of-the-art in modeling, analysis and tools. Comput. Sci. Rev. 15, 29–62 (2015)

    Article  MathSciNet  Google Scholar 

  15. Schneier, B.: Attack trees: modeling security threats. Dr. Dobb’s J. Softw. Tools 24(12), 21–29 (1999)

    Google Scholar 

  16. Tancrez, J.S., Semal, P., Chevalier, P.: Histogram based bounds and approximations for production lines. Eur. J. of Oper. Res. 197(3), 1133–1141 (2009)

    Article  Google Scholar 

  17. Widel, W., Audinot, M., Fila, B., Pinchinat, S.: Beyond 2014: formal methods for attack tree-based security modeling. ACM Comput. Surv. 52(4), 75:1–75:36 (2019)

    Google Scholar 

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Correspondence to Nihal Pekergin .

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Pekergin, N., Tan, S. (2021). Quantitative Analysis of Attack Defense Trees. In: Zhao, Q., Xia, L. (eds) Performance Evaluation Methodologies and Tools. VALUETOOLS 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 404. Springer, Cham. https://doi.org/10.1007/978-3-030-92511-6_13

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  • DOI: https://doi.org/10.1007/978-3-030-92511-6_13

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