ACM Home Page
Please provide us with feedback. Feedback
Rights protection for relational data
Full text PdfPdf (230 KB)
Source International Conference on Management of Data archive
Proceedings of the 2003 ACM SIGMOD international conference on Management of data table of contents
San Diego, California
SESSION: Data security and protection table of contents
Pages: 98 - 109  
Year of Publication: 2003
ISBN:1-58113-634-X
Authors
Radu Sion  Purdue University West Lafayette, IN
Mikhail Atallah  Purdue University West Lafayette, IN
Sunil Prabhakar  Purdue University West Lafayette, IN
Sponsor
SIGMOD: ACM Special Interest Group on Management of Data
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 11,   Downloads (12 Months): 104,   Citation Count: 15
Additional Information:

abstract   references   cited by   index terms   collaborative colleagues  

Tools and Actions: Request Permissions Request Permissions    Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/872757.872772
What is a DOI?

ABSTRACT

Protecting rights over relational data is of ever increasing interest, especially considering areas where sensitive, valuable content is to be outsourced. A good example is a data mining application, where data is sold in pieces to parties specialized in mining it.Different avenues for rights protection are available, each with its own advantages and drawbacks. Enforcement by legal means is usually ineffective in preventing theft of copyrighted works, unless augmented by a digital counter-part, for example watermarking.Recent research of the authors introduces the issue of digital watermarking for generic number sets. In the present paper we expand on this foundation and introduce a solution for relational database content rights protection through watermarking.Our solution addresses important attacks, such as data re-sorting, subset selection, linear data changes (applying a linear transformation on arbitrary subsets of the data). Our watermark also survives up to 50% and above data loss.Finally we present wmdb.*, a proof-of-concept implementation of our algorithm and its application to real life data, namely in watermarking the outsourced Wal-Mart sales data that we have available at our institute.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
M. J. Atallah and Jr. S. S. Wagstaff. Watermarking with quadratic residues. In Proc. of IS-T/SPIE Conf. on Security and Watermarking of Multimedia Contents, SPIE Vol. 3657, pp. 283--288., 1999.
 
2
 
3
4
 
5
Christian Collberg and Clark Thomborson. On the limits of software watermarking, August 1998.
 
6
Ingemar Cox, Jeffrey Bloom, and Matthew Miller. Digital watermarking. In Digital Watermarking. Morgan Kaufmann, 2001.
 
7
Stefan Katzenbeisser (editor) and Fabien Petitcolas (editor). Information hiding techniques for steganography and digital watermarking. In Information Hiding Techniques for Steganography and Digital Watermarking. Artech House, 2001.
 
8
J. Hale, J. Threet, and S. Shenoi. A framework for high assurance security of distributed objects, 1997.
 
9
10
 
11
J. Kiernan and R. Agrawal. Watermarking relational databases. In Proceedings of the 28th International Conference on Very Large Databases VLDB, 2002.
 
12
 
13
 
14
 
15
 
16
Radu Sion, Mikhail Atallah, and Sunil Prabhakar. On watermarking numeric sets. In Proceedings of IWDW 2002, Lecture Notes in Computer Science, CERIAS TR 2001-60. Springer-Verlag, 2002.
 
17
Radu Sion, Mikhail Atallah, and Sunil Prabhakar. On watermarking semistructures. In (submission for review), CERIAS TR 2001-54, 2002.
 
18

CITED BY  16

Collaborative Colleagues:
Radu Sion: colleagues
Mikhail Atallah: colleagues
Sunil Prabhakar: colleagues