Rights Protection for Data Cubes

  • Jie Guo
  • Yingjiu Li
  • Robert H. Deng
  • Kefei Chen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4176)


We propose a rights protection scheme for data cubes. The scheme embeds ownership information by modifying a set of selected cell values. The embedded message will not affect the usefulness of data cubes in the sense that the sum queries at any aggregation level are not affected. At the same time, the errors introduced to individual cell values are under control. The embedded message can be detected with a high probability even in the presence of typical data cube attacks. The proposed scheme can thus be used for protecting data cubes from piracy in an open, distributed environment.


Relational Database Watermark Scheme Data Cube Balance Cell Watermark Embedding 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Agrawal, R., Haas, P.J., Kiernan, J.: Watermarking relational data: framework, algorithms and analysis. The VLDB Journal 12(2), 157–169 (2003)CrossRefGoogle Scholar
  2. 2.
    Agrawal, R., Kiernan, J.: Watermarking relational databases. In: Proceedings of the 28th VLDB Conference, pp. 155–166 (2002)Google Scholar
  3. 3.
    Atallah, M.: A survey of watermarking techniques for non-media digital objects (invited talk). In: ACSW Frontiers 2005, p. 73 (2005)Google Scholar
  4. 4.
    Atallah, M., Raskin, V., Hempelmann, C., Karahan, M., Sion, R., Topkara, U., Triezenberg, K.: Natural language watermarking and tamperproofing. In: Fifth International Information Hiding Workshop, pp. 196–212 (2002)Google Scholar
  5. 5.
    Atallah, M., Wagstaff, S.: Watermarking with quadratic residues. In: Proceedings of IS&T/SPIE Conference on Security and Watermarking of Multimedia Contents, January 1999, vol. 3657, pp. 283–288 (1999)Google Scholar
  6. 6.
    Bellare, M., Canetti, R., Krawczyk, H.: Keying hash functions for message authentication. In: Koblitz, N. (ed.) CRYPTO 1996. LNCS, vol. 1109, pp. 1–15. Springer, Heidelberg (1996)Google Scholar
  7. 7.
    Bertino, E., Ooi, B., Yang, Y., Deng, R.: Privacy and ownership preserving of outsourced medical data. In: Proceedings of the 21st International Conference on Data Engineering, pp. 521–532 (2005)Google Scholar
  8. 8.
    Collberg, C., Thomborson, C.: Software watermarking: Models and dynamic embeddings. In: Proceedings of the 26th ACM SIGPLAN-SIGACT on Principles of Programming Languages, pp. 311–324 (1999)Google Scholar
  9. 9.
    Cox, I., Kilian, J., Leighton, T., Shamoon, T.: Secure spread spectrum watermarking for multimedia. IEEE Transactions on Image Processing 6(12), 1673–1687 (1997)CrossRefGoogle Scholar
  10. 10.
    Cox, I., Miller, M., Bloom, J.: Digital Watermarking: Principles and Practice. Morgan Kaufmann, San Francisco (2001)Google Scholar
  11. 11.
    Gray, J., Chaudhuri, S., Bosworth, A., Layman, A., Reichart, D., Venkatrao, M., Pellow, F., Pirahesh, H.: Data cube: A relational aggregation operator generalizing group-by, cross-tab, and sub-totals. Data Mining and Knowledge Discovery 1(1), 29–53 (1997)CrossRefGoogle Scholar
  12. 12.
    Gross-Amblard, D.: Query-preserving watermarking of relational databases and xml documents. In: Proceedings of the 19th ACM Symposium on Principles of Database Systems (PODS), pp. 191–201 (2003)Google Scholar
  13. 13.
    Hachez, G., Quisquater, J.: Which directions for asymmetric watermarking. In: Proceedings of XI European Signal Processing Conference (EUSIPCO), vol. I, pp. 283–286 (2002)Google Scholar
  14. 14.
    Johnson, N.F., Duric, Z., Jajodia, S.: Information Hiding: Steganography and Watermarking - Attacks and Countermeasures. Kluwer Academic, Dordrecht (2000)Google Scholar
  15. 15.
    Katzenbeisser, S., Petitcolas, F.: Information Hiding Techniques for Steganography and Digital Watermarking, Artech House (January 2000)Google Scholar
  16. 16.
    Krawczyk, H., Bellare, M., Canetti, R.: Hmac: Keyed-hashing for message authentication. In: Internet RFC 2104 (February 1997)Google Scholar
  17. 17.
    Li, Y., Swarup, V., Jajodia, S.: Fingerprinting relational databases: Schemes and specialties. IEEE Transactions on Dependable and Secure Computing 2(1), 34–45 (2005)CrossRefGoogle Scholar
  18. 18.
    Safavi-Naini, R.: Tracing traitors: a selective survey. In: Digital Rights Management Workshop, p. 72 (2004)Google Scholar
  19. 19.
    Sion, R.: Resilient rights protection for sensor streams. In: Proceedings of the Very Large Databases Conference, pp. 732–743 (2004)Google Scholar
  20. 20.
    Sion, R., Atallah, M., Prabhakar, S.: Rights protection for relational data. IEEE Transactions on Knowledge and Data Engineering 16(12), 1509–1525 (2004)CrossRefGoogle Scholar
  21. 21.
    Sion, R., Atallah, M., Prabhakar, S.: Rights protection for categorical data. IEEE Transactions on Knowledge and Data Engineering 17(7), 912–926 (2005)CrossRefGoogle Scholar
  22. 22.
    Wang, X., Yin, Y.L., Yu, H.: Finding collisions in the full SHA-1. In: Shoup, V. (ed.) CRYPTO 2005. LNCS, vol. 3621, pp. 17–36. Springer, Heidelberg (2005), http://www.infosec.sdu.edu.cn/paper/sha1-crypto-auth-new-2-yao.pdf Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Jie Guo
    • 1
    • 2
  • Yingjiu Li
    • 1
  • Robert H. Deng
    • 1
  • Kefei Chen
    • 2
  1. 1.School of Information SystemsSingapore Management UniversitySingapore
  2. 2.School of Information Security EngineeringShanghai Jiaotong UniversityChina

Personalised recommendations