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Oblivious user management for cloud-based data synchronization

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Abstract

One of the main issues with data sharing in cloud environment is to manage user access and its auto revocation in a controlled and flexible way. The issue becomes more complex when privacy on user access has to be ensured as well to hide additional leakage of information. For automatic revocation over cloud data, access can be bounded within certain anticipated time limit so that the access expires beyond effective time period. This time-oriented approach is more rigid and not a one-size-fits-all solution. In certain circumstances, exact time anticipation is not an easy choice. Instead, the alternate solution could be task oriented to restrict user beyond certain number of permissible attempts to access the data. We have proposed oblivious user management (OUM) in which a user can have access on cloud data for certain number of attempts without imposing any time restriction. For user authorization and her subsequent revocation, owner will perform one time setup activity and that is same for all users. The model also alleviates the burden of managing different access parameters at user end with each request as she will always use the same parameter for all valid attempts. Our approach also conceals the privacy of user attempts throughout the communication. Hiding this information helps to avoid distinguishing importance of particular user that has more authorization over others. Evaluation results have proved that OUM hides \((N-1)\) number of permissible attempts until \(N\mathrm{th}\) request arrives at Cloud Storage. The Performance analysis conducted on Google App Engine revealed that the cost of operations performed in OUM is within the range of 0.097–0.278 $ per 1,000 requests.

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Acknowledgments

This research was supported by a grant from the Kyung Hee University in 2013[KHU-20130439].

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Authors and Affiliations

  1. Ubiquitous Computing Lab, Department of Computer Engineering, Kyung Hee University, Global Campus, 1 Seocheon-dong, Giheung-gu, Yongin-si, Gyeonggi-do, 446-701, South Korea

    Mahmood Ahmad, Taechoong Cheong & Sungyoung Lee

  2. School of Computing, University of the West of Scotland, Paisley, PA1 2BE, UK

    Zeeshan Pervez

Authors
  1. Mahmood Ahmad
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  2. Zeeshan Pervez
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  4. Sungyoung Lee
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Corresponding author

Correspondence to Taechoong Cheong.

Appendix: Performance evaluation: Data tables

Appendix: Performance evaluation: Data tables

Performance evaluation presented in Sects. 6 and 7 is based on the following data tables. Figure 3 presented the visual representation of Table  2. Similarly, Figs. 4, 5, 6, 7, 8 are represented by Tables 3, 4, 5, 6 and 7 respectively.

Table 2 Time required for initial setup by owner and request evaluation at TTP with variable key length
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Table 3 Cost analysis and execution time at F4 instance of Google cloud
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Table 4 Execution time on android and Google app engine
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Table 5 Execution time for different numbers of attempts(10,500,1000) where key size is 1024 for all
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Table 6 Values of users request after evaluation at CSP, i.e., \(\Delta _{y_{1 \ldots n}}\) (without randomization)
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Table 7 Values of users request after evaluation at CSP, i.e., \(\Delta _{y_{1 \ldots n}}\) (with randomization)
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Ahmad, M., Pervez, Z., Cheong, T. et al. Oblivious user management for cloud-based data synchronization. J Supercomput 71, 1378–1400 (2015). https://doi.org/10.1007/s11227-014-1369-5

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