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Multiple Sensitive Association Protection in the Outsourced Database

  • Xiao Jiang
  • Jun Gao
  • Tengjiao Wang
  • Dongqing Yang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5982)

Abstract

With the popularity of the outsourced database, protecting sensitive associations in this environment is greatly desired and receives high attention. Table decomposition based method, which is suited for the current query evaluation of the database engine, provides an alternative to the conventional encryption method. Although some work on table decomposition has been done to handle single sensitive association in data publishing scenario or multiple associations in multiple servers, fewer attempts have been made to deal with multiple associations in single outsourced database. In this paper, we first illustrate that the simple extension of existing work will lead to new kinds of information leakages, and then we propose a novel table decomposition method, which achieves l-diversity, defeats the new information leakages, while at the same time, considers the query efficiency over the decomposed sub-tables. The final experimental results validate the effectiveness and efficiency of our method.

Keywords

Functional Dependency Query Processing Information Leakage Query Evaluation Query Performance 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Microsoft sql server data service, http://www.microsoft.com/azure/data.mspx
  2. 2.
    Simple database in amazon, http://aws.amazon.com/simpledb/
  3. 3.
    Aggarwal, G., Bawa, M., Ganesan, P., et al.: Two can keep a secret: A distributed architecture for secure database services. In: Proc. of CIDR, pp. 186–199 (2005)Google Scholar
  4. 4.
    Agrawal, R., Kiernan, J., Srikant, R., Xu, Y.: Order preserving encryption for numeric data. In: Proc. of SIGMOD, pp. 563–574 (2004)Google Scholar
  5. 5.
    Chung, S.S., Ozsoyoglu, G.: Processing Aggregation Queries over Encrypted Databases. In: Proc. of ICDE (2006)Google Scholar
  6. 6.
    Damiani, E., Vimercati, S.D.C., Jajodia, S., et al.: Balancing confidentiality and efficiency in untrusted relational DBMSs. In: Proc. of CCS, pp. 93–102 (2003)Google Scholar
  7. 7.
    Hacigümüş, H., Iyer, B., Li, C., Mehrotra, S.: Executing SQL over encrypted data in the database-service-provider model. In: Proc. of SIGMOD, pp. 216–227 (2002)Google Scholar
  8. 8.
    Hore, B., Mehrotra, S., Tsudik, G.: A privacy-preserving index for range queries. In: Proc. of VLDB, pp. 720–731 (2004)Google Scholar
  9. 9.
    Kambayashi, Y., Yoshikawa, M., Yajima, S.: Query processing for distributed databases using generalized semi-joins. In: Proc. of SIGMOD, pp. 151–160 (1982)Google Scholar
  10. 10.
    Li, J., Omiecinski, E.R.: Efficiency and security trade-off in supporting range queries on encrypted databases. In: DBSec, pp. 69–83 (2005)Google Scholar
  11. 11.
    Xiao, X., Tao, Y.: Anatomy: Simple and effective privacy preservation. In: Proc. of VLDB, pp. 139–150 (2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Xiao Jiang
    • 1
  • Jun Gao
    • 1
  • Tengjiao Wang
    • 1
  • Dongqing Yang
    • 1
  1. 1.Key Laboratory of High Confidence Software Technologies Department of Computer SciencePeking UniversityBeijingChina

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