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Distributed Differential Evolution for Anonymity-Driven Vertical Fragmentation in Outsourced Data Storage

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Web Information Systems Engineering – WISE 2020 (WISE 2020)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12343))

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Vertical fragmentation is a promising technique for outsourced data storage. It can protect data privacy while conserving original data without any transformation. Previous vertical fragmentation approaches need to predefine sensitive associations in data as the optimization objective, therefore unavailable for the data lacking related prior knowledge. Inspired by the anonymity measurement in anonymity approaches such as k-anonymity, an anonymity-driven vertical fragmentation problem is defined in this paper. To tackle this problem, a set-based distributed differential evolution (S-DDE) algorithm is proposed. An island model containing four sub-populations is adopted to improve population diversity and search efficiency. Two set-based update operators, i.e., set-based mutation operator and set-based crossover operator, are designed to transfer the calculation of discrete values to corresponding sets in vertical fragmentation. Extensive experiments are carried out, and the performance of S-DDE on anonymity-driven vertical fragmentation is verified. The computation efficiency of S-DDE is investigated, and the effectiveness of the generated vertical fragmentation solution by S-DDE is confirmed.

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  1. 1.


  1. Aggarwal, G., et al.: Two can keep a secret: a distributed architecture for secure database services. In: CIDR 2005 (2005)

    Google Scholar 

  2. Ciriani, V., De Capitani di Vimercati, S., Foresti, S., Jajodia, S., Paraboschi, S., Samarati, P.: Fragmentation and encryption to enforce privacy in data storage. In: Biskup, J., López, J. (eds.) ESORICS 2007. LNCS, vol. 4734, pp. 171–186. Springer, Heidelberg (2007).

    Chapter  Google Scholar 

  3. Ciriani, V., Vimercati, S.D.C.D., Foresti, S., Jajodia, S., Paraboschi, S., Samarati, P.: Combining fragmentation and encryption to protect privacy in data storage. ACM Trans. Inf. Syst. Secur. 13(3), 22 (2010)

    Article  Google Scholar 

  4. Gao, Z., Pan, Z., Zuo, C., Gao, J., Xu, Z.: An optimized deep network representation of multimutation differential evolution and its application in seismic inversion. IEEE Trans. Geosci. Remote Sens. 57(7), 4720–4734 (2019).

    Article  Google Scholar 

  5. Ge, Y.F., et al.: Distributed differential evolution based on adaptive mergence and split for large-scale optimization. IEEE Trans. Cybern. 48(7), 2166–2180 (2018).

    Article  Google Scholar 

  6. Köhler, J., Jünemann, K., Hartenstein, H.: Confidential database-as-a-service approaches: taxonomy and survey. J. Cloud Comput. 4(1), 1 (2015)

    Article  Google Scholar 

  7. Li, J., Yao, W., Zhang, Y., Qian, H., Han, J.: Flexible and fine-grained attribute-based data storage in cloud computing. IEEE Trans. Serv. Comput. 10(5), 785–796 (2017).

    Article  Google Scholar 

  8. Li, M., Sun, X., Wang, H., Zhang, Y., Zhang, J.: Privacy-aware access control with trust management in web service. World Wide Web 14(4), 407–430 (2011).

    Article  Google Scholar 

  9. Machanavajjhala, A., Gehrke, J., Kifer, D., Venkitasubramaniam, M.: L-diversity: privacy beyond k-anonymity. In: 22nd International Conference on Data Engineering. IEEE (2006).

  10. Peng, M., Zeng, G., Sun, Z., Huang, J., Wang, H., Tian, G.: Personalized app recommendation based on app permissions. World Wide Web 21(1), 89–104 (2017).

    Article  Google Scholar 

  11. Price, K., Storn, R.M., Lampinen, J.A.: Differential evolution: a practical approach to global optimization. Springer Science & Business Media, Heidelberg (2006)

    Google Scholar 

  12. Price, K.V.: Differential evolution. In: Handbook of Optimization, pp. 187–214. Springer, Heidelberg (2013)

    Google Scholar 

  13. Rani, K., Sagar, R.K.: Enhanced data storage security in cloud environment using encryption, compression and splitting technique. In: 2017 2nd International Conference on Telecommunication and Networks (TEL-NET). IEEE (2017).

  14. SWEENEY, L.: K-anonymity: a model for protecting privacy. Int. J. Uncertainty, Fuzziness Knowl. Based Syst. 10(05), 557–570 (2002).

  15. UbaidurRahman, N.H., Balamurugan, C., Mariappan, R.: A novel dna computing based encryption and decryption algorithm. Procedia Comput. Sci. 46, 463–475 (2015)

    Article  Google Scholar 

  16. De Capitani di Vimercati, S., Foresti, S., Jajodia, S., Livraga, G., Paraboschi, S., Samarati, P.: Loose associations to increase utility in data publishing. J. Comput. Secur. 23(1), 59–88 (2015)

    Google Scholar 

  17. Wang, H., Wang, Y., Taleb, T., Jiang, X.: Special issue on security and privacy in network computing. World Wide Web 23(2), 951–957 (2020).

    Article  Google Scholar 

  18. Wang, H., Zhang, Z., Taleb, T.: Special issue on security and privacy of IoT. World Wide Web 21(1), 1–6 (2018)

    Article  Google Scholar 

  19. Xu, X., Xiong, L., Liu, J.: Database fragmentation with confidentiality constraints: a graph search approach. In: 2015 ACM Conference on Data and Application Security and Privacy, pp. 263–270 (2015)

    Google Scholar 

  20. Yu, Y., Au, M.H., Ateniese, G., Huang, X., Susilo, W., Dai, Y., Min, G.: Identity-based remote data integrity checking with perfect data privacy preserving for cloud storage. IEEE Trans. Inf. Forensics Secur. 12(4), 767–778 (2017)

    Article  Google Scholar 

  21. Zhang, F., Wang, Y., Liu, S., Wang, H.: Decision-based evasion attacks on tree ensemble classifiers. World Wide Web (2020).

    Article  Google Scholar 

  22. Zhang, J., Tao, X., Wang, H.: Outlier detection from large distributed databases. World Wide Web 17(4), 539–568 (2014)

    Article  Google Scholar 

  23. Zhang, Y., Chen, X., Li, J., Wong, D.S., Li, H., You, I.: Ensuring attribute privacy protection and fast decryption for outsourced data security in mobile cloud computing. Inf. Sci. 379, 42–61 (2017).

    Article  MATH  Google Scholar 

  24. Zheng, L.M., Zhang, S.X., Zheng, S.Y., Pan, Y.M.: Differential evolution algorithm with two-step subpopulation strategy and its application in microwave circuit designs. IEEE Trans. Industr. Inf. 12(3), 911–923 (2016).

    Article  Google Scholar 

  25. Zhou, X.G., Peng, C.X., Liu, J., Zhang, Y., Zhang, G.J.: Underestimation-assisted global-local cooperative differential evolution and the application to protein structure prediction. IEEE Trans. Evol. Comput., 1 (2019).

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Correspondence to Zhenxiang Chen .

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Ge, YF., Cao, J., Wang, H., Zhang, Y., Chen, Z. (2020). Distributed Differential Evolution for Anonymity-Driven Vertical Fragmentation in Outsourced Data Storage. In: Huang, Z., Beek, W., Wang, H., Zhou, R., Zhang, Y. (eds) Web Information Systems Engineering – WISE 2020. WISE 2020. Lecture Notes in Computer Science(), vol 12343. Springer, Cham.

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  • Print ISBN: 978-3-030-62007-3

  • Online ISBN: 978-3-030-62008-0

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