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Data survivability vs. security in information systems

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  • Levitin, Gregory
  • Hausken, Kjell
  • Taboada, Heidi A.
  • Coit, David W.

Abstract

A multiple objective problem formulation and solution methodology is presented to select optimal information and data storage configurations considering both data survivability and data security, as well as cost. This paper considers a situation where the information is divided into several separately stored blocks in order to mitigate the risk of unauthorized access or theft. The information can be used only if all of the blocks are accessed. To impede the information theft, the defender prefers to maximize the number of blocks. On the other hand the destruction of any block destroys the integrity of information and makes it impossible to use. To impede the information destruction, the defender prefers to maximize the number of parallel (reserve) copies of each block, regardless how many blocks in series there are. Given the set of available information storage resources, the defender must consider a multi-objective optimization problem to determine how many blocks and their copies to create, and how to distribute them among available resources in order to minimize information vulnerability, insecurity, and storage cost. Non-dominated solutions to this problem are determined using a multiple objective genetic algorithm (MOGA). This methodology is demonstrated with two general examples.

Suggested Citation

  • Levitin, Gregory & Hausken, Kjell & Taboada, Heidi A. & Coit, David W., 2012. "Data survivability vs. security in information systems," Reliability Engineering and System Safety, Elsevier, vol. 100(C), pages 19-27.
    • Handle: RePEc:eee:reensy:v:100:y:2012:i:c:p:19-27
    DOI: 10.1016/j.ress.2011.12.015
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    References listed on IDEAS

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    Cited by:

    1. Chołda, Piotr & Følstad, Eirik L. & Helvik, Bjarne E. & Kuusela, Pirkko & Naldi, Maurizio & Norros, Ilkka, 2013. "Towards risk-aware communications networking," Reliability Engineering and System Safety, Elsevier, vol. 109(C), pages 160-174.
    2. Levitin, Gregory & Xing, Liudong & Xiang, Yanping, 2020. "Optimization of time constrained N-version programming service components with competing task execution and version corruption processes," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    3. Kjell Hausken & Jonathan W. Welburn, 2021. "Attack and Defense Strategies in Cyber War Involving Production and Stockpiling of Zero-Day Cyber Exploits," Information Systems Frontiers, Springer, vol. 23(6), pages 1609-1620, December.
    4. Levitin, Gregory & Xing, Liudong & Xiang, Yanping, 2020. "Optimal early warning defense of N-version programming service against co-resident attacks in cloud system," Reliability Engineering and System Safety, Elsevier, vol. 201(C).
    5. Levitin, Gregory & Xing, Liudong & Dai, Yuanshun, 2018. "Co-residence based data vulnerability vs. security in cloud computing system with random server assignment," European Journal of Operational Research, Elsevier, vol. 267(2), pages 676-686.
    6. Zhang, Xiaoyu & Xu, Maochao & Da, Gaofeng & Zhao, Peng, 2021. "Ensuring confidentiality and availability of sensitive data over a network system under cyber threats," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
    7. Ben Yaghlane, Asma & Azaiez, M. Naceur, 2017. "Systems under attack-survivability rather than reliability: Concept, results, and applications," European Journal of Operational Research, Elsevier, vol. 258(3), pages 1156-1164.
    8. Guizhou Wang & Jonathan W. Welburn & Kjell Hausken, 2020. "A Two-Period Game Theoretic Model of Zero-Day Attacks with Stockpiling," Games, MDPI, vol. 11(4), pages 1-26, December.
    9. Xing, Liudong & Levitin, Gregory, 2017. "Balancing theft and corruption threats by data partition in cloud system with independent server protection," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 248-254.
    10. Gregory Levitin & Liudong Xing & Hong‐Zhong Huang, 2019. "Security of Separated Data in Cloud Systems with Competing Attack Detection and Data Theft Processes," Risk Analysis, John Wiley & Sons, vol. 39(4), pages 846-858, April.
    11. Luo, Liang & Xing, Liudong & Levitin, Gregory, 2019. "Optimizing dynamic survivability and security of replicated data in cloud systems under co-residence attacks," Reliability Engineering and System Safety, Elsevier, vol. 192(C).
    12. Heping Jia & Rui Peng & Yi Ding & Changzheng Shao, 2020. "Reliability analysis of distributed storage systems considering data loss and theft," Journal of Risk and Reliability, , vol. 234(2), pages 303-321, April.
    13. Peng, Rui & Xiao, Hui & Guo, Jianjun & Lin, Chen, 2020. "Optimal defense of a distributed data storage system against hackers’ attacks," Reliability Engineering and System Safety, Elsevier, vol. 197(C).

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