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Design and modeling of moving target defense in workflow-based applications

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Abstract

This paper analyzes the tradeoffs between performance and resilience against cyber attacks of applications organized as workflows. The static nature of current workflows is a major benefit to attackers. To combat this advantage, a promising new approach inspired to Moving Target Defense (MTDs) was developed to increase a workflow’s robustness to cyber attacks. This approach is based on dynamic reconfigurations of workflow tasks to reduce an attacker’s probability of succeeding in completing the reconnaissance phase before launching an attack. Dynamic reconfigurations increase the resilience of a workflow against cyber attacks but increase its execution time due to the overhead of reconfigurations. As a part of this paper, we developed metrics that capture the impact of reconfigurations on a workflow’s execution time and resilience against cyber attacks. The paper also presents recursive algorithms for computing the execution time and the reconnaissance function of a workflow. Our analysis relied on extensive trace-driven simulations of workflows from five different traces from the Workflow Trace Archive (WTA) and we used 6000 workflows from three different domains: scientific computing, engineering, and industrial. Our analysis of the results showed that there is a significant difference at the 95% confidence level due to reconfiguration on the resilience of workflows and demonstrated a consistent behavior across all five trace domains.

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References

  1. Menascé, D.A., Casallicchio, E., Dubey, V.: On optimal service selection in service oriented architectures. Perform. Eval. 67(8):659–675 (2010). August, Special Issue on Software and Performance

  2. van der Aalst, W.M.P., van Hee, K.M .: Workflow Management: Models, Methods, and Systems. MIT Press, Cambridge (2002)

  3. Goble, C.A., De Roure, D.C.: myExperiment: social networking for workflow-using e-scientists. In: Proceedings of the 2nd Workshop on Workflows in Support of Large-Scale Science, vol. 7, pp. 1–2, New York, NY. Association for Computing Machinery (2007)

  4. Deelman, E., Peterka, T., Altintas, I., Carothers, C.D., van Dam, K.K., Moreland, K., Parashar, M., Ramakrishnan, L., Taufer, M., Vetter, J.: The future of scientific workflows. Intl. J. High Perform. Comput. Appl. 32(1):159–175, (2018)

  5. Fuhui, W., Qingbo, W., Tan, Y.: Workflow scheduling in cloud: a survey. J. Supercomput. 71(9), 3373–3418 (2015)

    Article  Google Scholar 

  6. Dubey, V.K., Menascé, D.A.: Utility-based optimal service selection for business processes in service oriented architectures. In: 2010 IEEE Intl. Conf. Web Services, pp. 542–550. IEEE (2010)

  7. OASIS Committee. Web Service—Business Process Execution Language (WS BPEL)—Version 2.0—OASIS Committee Draft. OASIS, May (2006)

  8. Versluis, L., van Eyk, E., Iosup, A.: An analysis of workflow formalisms for workflows with complex non-functional requirements. In: Companion of the 2018 ACM/SPEC Intl. Conf. Performance Engineering, ICPE ’18, pp. 107–112, New York, NY. ACM. (2018)

  9. Martin, Lockheed.: Gaining the Advantage: applying Cyber Kill Chain methodology to network defense. Lockeed, (2015)

  10. Connell, W., Menascé, D.A., Albanese, M.: Performance modeling of moving target defenses. In: Proc. 2017 Workshop on Moving Target Defense, MTD ’17, pp. 53–63, New York, NY. ACM (2017)

  11. Connell, W., Menascé, D.A., Albanese, M.: Performance modeling of moving target defenses with reconfiguration limits. IEEE Trans. Depend. Secure Comput. 18(1), 205–219 (2021)

    Article  Google Scholar 

  12. Alhozaimy, S., Menascé, D.A.: A formal analysis of performance-security tradeoffs under frequent task reconfigurations. Future Gener. Comput. Syst. 127, 252–262 (2022)

    Article  Google Scholar 

  13. Versluis, L., Matha, R., Talluri, S., Hegeman, T., Prodan, R., Deelman, E., Iosup, A.: The workflow trace archive: open-access data from public and private computing infrastructures. IEEE Trans. Parallel Distrib. Syst. 31(9):2170–2184.

    Google Scholar 

  14. Versluis, L., Neacsu, M., Iosup, A.: A trace-based performance study of autoscaling workloads of workflows in datacenters. In: 2018 18th IEEE/ACM Intl. Symp. Cluster, Cloud and Grid Computing (CCGRID), pp. 223–232, May (2018)

  15. Kephart, J.O., Chess, D.M.: The vision of autonomic computing. Computer 36(1), 41–50 (2003)

    Article  MathSciNet  Google Scholar 

  16. Ward, B.C., Gomez, S.R., Skowyra, R.W., Martin, J.N., Landry, J.W.: Survey of Cyber Moving Targets, 2nd edn. Technical Report January, MIT, Cambridge (2018)

    Google Scholar 

  17. Sengupta, S., Chowdhary, A., Sabur, A., Alshamrani, A., Huang, D., Kambhampati, S.: A survey of moving target defenses for network security. IEEE Commun. Surveys Tutor. 1 (2020)

  18. Dsouza, G., Hariri, S., Al-Nashif, Y., Rodriguez, G.: Resilient dynamic data driven application systems (rDDDAS). Procedia Comput. Sci. 18, 1929–1938 (2013)

    Article  Google Scholar 

  19. Tunc, C., Fargo, F., Al-Nashif, Y., Hariri, S., Hughes, J.: Autonomic resilient cloud management (ARCM) design and evaluation. In: 2014 International Conference on Cloud and Autonomic Computing, pp. 44–49 (2014)

  20. Hallerbach, A., Bauer, T., Reichert, M.: Capturing variability in business process models: the Provop approach. J. Softw. Maint. Evol. Res. Pract. 22(6–7), 519–546 (2010)

    Article  Google Scholar 

  21. Marrella, A., Mecella, M., Sardina, S.: Intelligent process adaptation in the smartpm system. ACM Trans. Intell. Syst. Technol. 8(2) (2016)

  22. Gao, H., Huang, W., Yang, X., Duan, Y., Yin, Y.: Toward service selection for workflow reconfiguration:an interface-based computing solution. Future Gener. Comput. Syst. 87, 298–311 (2018)

    Article  Google Scholar 

  23. Gao, H., Huang, W., Duan, Y.: The cloud-edge-based dynamic reconfiguration to service workflow for mobile ecommerce environments: a QoS prediction perspective. ACM Trans. Int. Technol. 21(1) (2021)

  24. Leitner, M., Rinderle-Ma, S.: A systematic review on security in process-aware information systems—constitution, challenges, and future directions. Inf. Softw. Technol. 56(3), 273–293 (2014)

    Article  Google Scholar 

  25. Anupa, J., Sekaran, K.C.: Cloud workflow and security: a survey. In: 2014 International Conference on Advances in Computing, Communications and Informatics (ICACCI), pp. 1598–1607 (2014)

  26. Wang, Y., Guo, Y., Guo, Z., Baker, T., Liu, W.: CLOSURE: a cloud scientific workflow scheduling algorithm based on attack-defense game model. Future Gener. Comput. Syst. 111, 460–474 (2020)

    Article  Google Scholar 

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Contributions

SA: Software development, experiment analysis, prepared figures, conceptualization, methodology, writing—original draft. DAM: Conceptualization, methodology, writing—original draft. MA: Conceptualization, methodology, visualization, review the manuscript.

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Correspondence to Sarah Alhozaimy.

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Alhozaimy, S., Menascé, D.A. & Albanese, M. Design and modeling of moving target defense in workflow-based applications. Cluster Comput 27, 945–958 (2024). https://doi.org/10.1007/s10586-023-03998-9

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