Applying watermarking for copyright protection, traitor identification and joint ownership: A review

Mohanpurkar, Arti; Joshi, Madhuri S.

doi:10.1109/wict.2011.6141387

Cited by 6 publications

(4 citation statements)

References 25 publications

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“…Watermark security is also ensured by checking the system against the attacks. Some recent surveys (Halder, Pal, & Cortesi, 2010;Mohanpurkar & Joshi, 2011) present a review of several watermarking techniques which apply different approaches to achieve ownership protection. A few techniques have attempted fingerprinting of relational databases and a very few have claimed for collusion secure fingerprinting.…”

Section: Related Workmentioning

confidence: 99%

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

Mohanpurkar

Joshi²

2016

International Journal of Ambient Computing and Intelligence

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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.

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Section: Related Workmentioning

confidence: 99%

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

Mohanpurkar

Joshi²

2016

International Journal of Ambient Computing and Intelligence

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“…As per the latest study [5], to the best of our knowledge no technique has been proposed yet which achieves fingerprinting in numeric relational database where distortion is minimum, decoding accuracy is 100% and performs traitor tracing. Fig.…”

Section: Related Workmentioning

confidence: 99%

A Fingerprinting Technique for Numeric Relational Databases with Distortion Minimization

Mohanpurkar

Joshi²

2015

2015 International Conference on Computing Communication Control and Automation

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With the ever-increasing usage of internet, the availability of digital data is in tremendous demand. In this context, it is essential to protect the ownership of the data and to be able to find the guilty user. In this paper, a fingerprinting scheme is proposed to provide protection for Numeric Relational Database (RDB), which focuses on challenges like: 1. Minimum distortion in Numeric database, 2. Usability preservation, 3. Nonviolation of the requirement of blind decoding. When the digital data in concern is numeric in nature the usability of data needs to be keenly preserved, this is made possible by achieving minimum distortion.

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“…Different approaches and types of watermarking numeric relational databases are suggested in [8,9,11,13] where information preservation and fingerprinting are not taken into consideration hence no question of collusion attack.…”

Section: Related Workmentioning

confidence: 99%

“…An exhaustive literature survey [10,11,13] done here helps us to conclude that there is a need for a system which is able to insert and detect fingerprints in numeric databases that preserves information and avoids collusion.…”

Section: Related Workmentioning

confidence: 99%

Fingerprinting Numeric Databases with Information Preservation and Collusion Avoidance

Mohanpurkar¹,

Joshi²

2015

IJCA

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Information age demands omnipresence of data. Large data sets are created, maintained and outsourced to the third party experts for data mining. Knowledge and patterns are extracted by using advanced data mining algorithms that assist the decision makers to ensure quick, correct and effective decisions to be made in this world of competition. The outsourcing of these large data sets faces the problem of theft and loss of ownership. The problem of data theft can be handled by fingerprinting i.e. embedding buyer specific marks along with ownership identification marks which further leads to the challenge of knowledge preservation. Thus, a technique which performs fingerprinting with knowledge preservation on numeric relational data to be outsourced is proposed here. It is ensured that the usability constraints are not violated. Knowledge preservation is achieved by optimizing the error to be inserted using Particle Swarm Optimization (PSO), a natureinspired optimization algorithm. Collusion attack is very well-known in the context of fingerprinting techniques. Here, the proposed system provides a mechanism for avoiding collusion. The proposed system is independent of the primary key.

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Applying watermarking for copyright protection, traitor identification and joint ownership: A review

Cited by 6 publications

References 25 publications

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

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

A Fingerprinting Technique for Numeric Relational Databases with Distortion Minimization

Fingerprinting Numeric Databases with Information Preservation and Collusion Avoidance

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