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A Traitor Identification Technique for Numeric Relational Databases with Distortion Minimization and Collusion Avoidance

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  • Arti Arun Mohanpurkar

    (Dr. D Y Patil School of Engineering &Technology, Lohgaon, Pune, Maharashtra, India)

  • Madhuri Satish Joshi

    (MGM's Jawaharlal Nehru Engineering College, Aurangabad, Maharashtra, India)

Abstract

An enormous growth in internet usage has resulted into great amounts of digital data to handle. Data sharing has become significant and unavoidable. Data owners want the data to be secured and perennially available. Data protection and any violations thereby become crucial. This work proposes a traitor identification system which securely embeds the fingerprint to provide protection for numeric relational databases. Digital data of numeric nature calls for preservation of usability. It needs to be done so by achieving minimum distortion. The proposed insertion technique with reduced time complexity ensures that the fingerprint inserted in the form of an optimized error leads to minimum distortion. Collusion attack is an integral part of fingerprinting and a provision to mitigate by avoiding the same is suggested. Robustness of the system against several attacks like tuple insertion, tuple deletion etc. is also depicted.

Suggested Citation

  • Arti Arun Mohanpurkar & Madhuri Satish Joshi, 2016. "A Traitor Identification Technique for Numeric Relational Databases with Distortion Minimization and Collusion Avoidance," International Journal of Ambient Computing and Intelligence (IJACI), IGI Global, vol. 7(2), pages 114-137, July.
    • Handle: RePEc:igg:jaci00:v:7:y:2016:i:2:p:114-137
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    1. Sankhadeep Chatterjee & Sarbartha Sarkar & Nilanjan Dey & Soumya Sen, 2018. "Non-Dominated Sorting Genetic Algorithm-II-Induced Neural-Supported Prediction of Water Quality with Stability Analysis," Journal of Information & Knowledge Management (JIKM), World Scientific Publishing Co. Pte. Ltd., vol. 17(02), pages 1-20, June.

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