International Journal of Mathematical, Engineering and Management Sciences

ISSN: 2455-7749

Survivability and Vulnerability Analysis of Cloud RAID Systems under Disk Faults and Attacks

Qisi Liu
Department of Electrical and Computer Engineering, University of Massachusetts, Dartmouth, MA, USA.

Liudong Xing
Department of Electrical and Computer Engineering, University of Massachusetts, Dartmouth, MA, USA.

DOI https://doi.org/10.33889/IJMEMS.2021.6.1.003

Received on May 14, 2020
  ;
Accepted on July 01, 2020

Abstract

In this paper we model and analyze survivability and vulnerability of a cloud RAID (Redundant Array of Independent Disks) storage system subject to disk faults and cyber-attacks. The cloud RAID survivability is concerned with the system’s ability to function correctly even under the circumstance of hazardous behaviors including disk failures and malicious attacks. The cloud RAID invulnerability is concerned with the system’s ability to function correctly while occupying some state immune to malicious attacks. A continuous-time Markov chains-based method is suggested to perform the disk level survivability and invulnerability analysis. Combinatorial methods are then presented for the cloud RAID system level analysis, which can accommodate both homogeneous (based on binomial coefficients) and heterogeneous (based on multi-valued decision diagrams) disks. A detailed case study on a cloud RAID 5 system is conducted to illustrate the application of the proposed methods. Impacts of different parameters on the disk and system survivability and invulnerability are also investigated through numerical analysis.

Keywords- Cloud storage system, Cyberattack, Disk fault, Survivability, Vulnerability.

Citation

Liu, Q., & Xing, L. (2021). Survivability and Vulnerability Analysis of Cloud RAID Systems under Disk Faults and Attacks. International Journal of Mathematical, Engineering and Management Sciences, 6(1), 15-29. https://doi.org/10.33889/IJMEMS.2021.6.1.003.

Conflict of Interest

The authors confirm that there is no conflict of interest to declare for this publication.

Acknowledgements

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. The authors would like to thank the editor and anonymous reviewers for their comments that help improve the quality of this work.

References

Ahmed, M.E., & Kim, H. (2017, April). DDoS attack mitigation in Internet of Things using software defined networking. In 2017 IEEE Third International Conference on Big Data Computing Service and Applications (pp. 271-276). IEEE. San Francisco, CA.

Avital, N., Zawoznik, A., Azaria, J., & Lambert, K. (2020). 2019 global DDoS threat landscape report. Imperva Research Labs, https://www.imperva.com/blog/2019-global-ddos-threat-landscape-report/, Accessed in May 2020.

Bamiah, M.A., & Brohi, S.N. (2011). Seven deadly threats and vulnerabilities in cloud computing. International Journal of Advanced Engineering Sciences and Technologies, 9(1), 87-90.

Check Point. (2020). Security report 2020. Check Point Software Technologies Ltd, https://www.bristol.de/wp-content/uploads/2020/03/2020-security-report.pdf, Accessed in May 2020.

Chou, T.S. (2013). Security threats on cloud computing vulnerabilities. International Journal of Computer Science & Information Technology, 5(3), 79.

Escudero, C., Sicard, F., & Zamaï, É. (2018, September). Process-aware model based IDSs for industrial control systems cybersecurity: approaches, limits and further research. In 2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA) (Vol. 1, pp. 605-612). IEEE. Funchal, Portugal.

Fung, C., Chen, Y.L., Wang, X., Lee, J., Tarquini, R., Anderson, M., & Linger, R. (2005, October). Survivability analysis of distributed systems using attack tree methodology. In MILCOM 2005-2005 IEEE Military Communications Conference (pp. 583-589). IEEE. Atlantic City, NJ.

George, G., & Thampi, S.M. (2018, September). A graph-based decision support model for vulnerability analysis in IoT networks. In International Symposium on Security in Computing and Communication (pp. 1-23). Springer, Singapore.

Hasan, M.M., & Rahman, M.A. (2020). A signaling game approach to mitigate co-resident attacks in an IaaS cloud environment. Journal of Information Security and Applications, 50, 102397.

Hummel, R. (2019). Netscout threat intelligence report. Netscout System INC, https://www.netscout.com/sites/default/files/2020-02/SECR_001_EN-2001_Web.pdf, Accessed in May 2020.

Iliadis, I., Sotnikov, D., Ta-Shma, P., & Venkatesan, V. (2014, November). Reliability of geo-replicated cloud storage systems. In 2014 IEEE 20th Pacific Rim International Symposium on Dependable Computing (pp. 169-179). IEEE. Singapore.

Ko, R., Lee, S.G., & Rajan, V. (2013). Cloud computing vulnerability incidents: a statistical overview. Cloud Security Alliance, https://crow.org.nz/sites/default/files/2017-01/Cloud_Computing_Vulnerability_Incidents.pdf, Accessed in May 2020.

Levitin, G., Xing, L., & Dai, Y. (2018). Co-residence based data vulnerability vs. security in cloud computing system with random server assignment. European Journal of Operational Research, 267(2), 676-686.

Liu, Q., & Xing, L. (2015a). Reliability modeling of cloud-RAID-6 storage system. International Journal of Future Computer and Communication, 4(6), 415-420.

Liu, Q., & Xing, L. (2015b). Hierarchical reliability analysis of multi-state cloud-RAID storage system. In Proc. of International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (pp. 1-7). Beijing, China.

Liu, Q., Xing, L., & Zhou, C. (2019). Probabilistic modeling and analysis of sequential cyber‐attacks. Engineering Reports, 1(4), e12065.

Mandava, L., & Xing, L. (2019). Balancing reliability and cost in cloud‐RAID systems with fault‐level coverage. International Journal of Mathematical, Engineering and Management Sciences, 4(5), 1068-1080.

Mandava, L., & Xing, L. (2020). Optimizing imperfect coverage cloud-RAID systems considering reliability and cost. International Journal of Reliability, Quality and Safety Engineering, 27(2), 2040001.

Mirkovic, J., & Reiher, P. (2004). A taxonomy of DDoS attack and DDoS defense mechanisms. ACM SIGCOMM Computer Communication Review, 34(2), 39-53.

Nachiappan, R., Javadi, B., Calheiros, R.N., & Matawie, K.M. (2017). Cloud storage reliability for big data applications: a state of the art survey. Journal of Network and Computer Applications, 97, 35-47.

Osanaiye, O., Choo, K.K.R., & Dlodlo, M. (2016). Distributed denial of service (DDoS) resilience in cloud: review and conceptual cloud DDoS mitigation framework. Journal of Network and Computer Applications, 67, 147-165.

Shahrad, M., Mosenia, A., Song, L., Chiang, M., Wentzlaff, D., & Mittal, P. (2018). Acoustic denial of service attacks on hard disk drives. In Proc. of the 2018 Workshop on Attacks and Solutions in Hardware Security (pp. 34–39). ACM, New York, USA, DOI: https://doi.org/10.1145/3266444.3266448.

Wang, B., Zheng, Y., Lou, W., & Hou, Y.T. (2015). DDoS attack protection in the era of cloud computing and software-defined networking. Computer Networks, 81, 308-319.

Widder, D.V. (2015). Laplace transform (PMS-6). Princeton university press. Princeton, NJ.

Xing, L. (2020). Reliability in Internet of Things: current status and future perspectives. IEEE Internet of Things Journal, in press, doi: 10.1109/JIOT.2020.2993216.

Xing, L., & Amari, S.V. (2015). Binary decision diagrams and extensions for system reliability analysis. Scrivener Publishing LLC, Beverly, MA and Wiley, doi:10.1002/9781119178026.

Xing, L., & Dai, Y.S. (2009). A new decision-diagram-based method for efficient analysis on multistate systems. IEEE Transactions on Dependable and Secure Computing, 6(3), 161-174.

Xing, L., Levitin, G., & Xiang, Y. (2019). Defending N-version programming service components against co-resident attacks in IoT cloud systems. IEEE Transactions on Services Computing, doi: 10.1109/TSC.2019.2904958.

Xu, S., Yang, G., Mu, Y., & Liu, X. (2019). A secure IoT cloud storage system with fine-grained access control and decryption key exposure resistance. Future Generation Computer Systems, 97, 284-294.

Zeng, Y., Xing, L., Zhang, Q., & Jia, X. (2019). An analytical method for reliability analysis of hardware‐software co‐design system. Quality and Reliability Engineering International, 35(1), 165-178.

Zhang, R., Lin, C., Meng, K., & Zhu, L. (2013, November). A modeling reliability analysis technique for cloud storage system. In 2013 15th IEEE International Conference on Communication Technology (pp. 32-36). IEEE. Guilin, China.

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