Please use this identifier to cite or link to this item: https://doi.org/10.1007/978-3-642-15546-8_10
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dc.titleA geometric approach for efficient licenses validation in DRM
dc.contributor.authorSachan, A.
dc.contributor.authorEmmanuel, S.
dc.contributor.authorKankanhalli, M.S.
dc.date.accessioned2013-07-04T07:58:11Z
dc.date.available2013-07-04T07:58:11Z
dc.date.issued2010
dc.identifier.citationSachan, A.,Emmanuel, S.,Kankanhalli, M.S. (2010). A geometric approach for efficient licenses validation in DRM. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 6358 LNCS : 132-149. ScholarBank@NUS Repository. <a href="https://doi.org/10.1007/978-3-642-15546-8_10" target="_blank">https://doi.org/10.1007/978-3-642-15546-8_10</a>
dc.identifier.isbn3642155456
dc.identifier.issn03029743
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/40168
dc.description.abstractIn DRM systems contents are distributed from the owner to consumers, often through multiple middle level distributors. The owner issues redistribution licenses to its distributors. The distributors using their received redistribution licenses can generate and issue new redistribution licenses to their sub-distributors and new usage licenses to consumers. For the rights violation detection, all the newly generated licenses must be validated. The validation process becomes complex when there exist multiple redistribution licenses for a content with the distributors. In such cases, it requires the validation using an exponential number of validation equations, which makes the validation process much computation-intensive. Thus to do the validation efficiently, in this paper we propose a method to geometrically derive the relationship between different validation equations to identify the redundant validation equations. These redundant validation equations are then removed using graph theory concepts. Experimental results show that the validation time can be significantly reduced using our proposed approach. © 2010 Springer-Verlag.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1007/978-3-642-15546-8_10
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentCOMPUTER SCIENCE
dc.description.doi10.1007/978-3-642-15546-8_10
dc.description.sourcetitleLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.description.volume6358 LNCS
dc.description.page132-149
dc.identifier.isiutNOT_IN_WOS
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