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Multi-modal fingerprinting for multimedia assets: optimisation of media security protection in online distribution environments

Thiemert, D. and Badii, A. (2008) Multi-modal fingerprinting for multimedia assets: optimisation of media security protection in online distribution environments. In: SSE Systems Engineering Conference 2008 , 25-26 Sep 2008, The University of Reading. (Unpublished)

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Since the advent of the internet in every day life in the 1990s, the barriers to producing, distributing and consuming multimedia data such as videos, music, ebooks, etc. have steadily been lowered for most computer users so that almost everyone with internet access can join the online communities who both produce, consume and of course also share media artefacts. Along with this trend, the violation of personal data privacy and copyright has increased with illegal file sharing being rampant across many online communities particularly for certain music genres and amongst the younger age groups. This has had a devastating effect on the traditional media distribution market; in most cases leaving the distribution companies and the content owner with huge financial losses. To prove that a copyright violation has occurred one can deploy fingerprinting mechanisms to uniquely identify the property. However this is currently based on only uni-modal approaches. In this paper we describe some of the design challenges and architectural approaches to multi-modal fingerprinting currently being examined for evaluation studies within a PhD research programme on optimisation of multi-modal fingerprinting architectures. Accordingly we outline the available modalities that are being integrated through this research programme which aims to establish the optimal architecture for multi-modal media security protection over the internet as the online distribution environment for both legal and illegal distribution of media products.

Item Type:Conference or Workshop Item (Paper)
Divisions:Science > School of Mathematical, Physical and Computational Sciences > Department of Computer Science
ID Code:1128


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