SEMI-FRAGILE WATERMARKING SCHEME FOR RELATIONAL DATABASE TAMPER DETECTION

Authors

  • Saeed Arif Shah Saudi Electronic University Riyadh, Kingdom of Saudi Arabia
  • Imran Ali Khan COMSATS University Islamabad, Abbottabad, Pakistan
  • Syed Zaki Hassan Kazmi University of AJK, Pakistan
  • Fariza Hanum Binti Md Nasaruddin Faculty of Computer Science and Information Technology, University of Malaya, 50603, Kuala Lumpur, Malaysia

DOI:

https://doi.org/10.22452/mjcs.vol34no1.1

Keywords:

Semi-fragile watermark, Relational Database Security, Integrity

Abstract

Most of data over the Internet today is hosted on outsourced third-party servers which are not trusted. Sometimes data is to be distributed to other organizations or individuals for pre-agreed use. In both of these scenarios data is susceptible to malicious tampering so there is a need for some mechanism to verify database integrity. Moreover, the authentication process should be able to differentiate between valid updates and malicious modifications. In this paper, we present a novel semi-fragile watermarking scheme for relational database integrity verification. Besides detection and localization of database tampering, the proposed scheme allows modifications to the data that need periodic updates, without requiring re-watermarking. Watermark embedding is distortion free, as it is done by adjusting the text case of selected data values resulting in retention of semantic meaning of data. Additionally, group-based embedding ensures the localization of tampering up to group level. We implemented a proof of concept application of our watermarking technique. Theoretical analysis and experiments show that even a single value modification can be detected with very high probability besides detection of attacks like tuple insertion and tuple deletion.

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Published

2021-01-28

How to Cite

Shah, S. A., Ali Khan, I., Hassan Kazmi, S. Z., & Binti Md Nasaruddin, F. H. (2021). SEMI-FRAGILE WATERMARKING SCHEME FOR RELATIONAL DATABASE TAMPER DETECTION. Malaysian Journal of Computer Science, 34(1), 1–12. https://doi.org/10.22452/mjcs.vol34no1.1

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