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• W18583860 abstract "Although Digital Rights Management (DRM) has been proven effective and successful in protecting the confidentiality of sensitive documents by providing access control, DRM products have not been widely adopted and used to their potential. One reason for this could be that cost and benefit of these products have not been analyzed in a systematic and quantitative manner to date. As a result, companies do not have an established procedure to evaluate the cost and benefit of implementing these products. In this document, the benefits of implementing DRM products in enterprises are quantified using stochastic Petri-net models and are compared with the security needs of a corporation and potential costs incurred by the implementation process. An evaluating procedure for implementing DRM products is established. This procedure has the potential to be used to improve the ability of a corporation to make sensible security investment decisions.The implementation of MS IRM (Microsoft Information Rights Management), one of the DRM products, was studied as a type case. In this case study, the MS IRM system was analyzed; a group of security metrics were developed for measuring and evaluating the effectiveness of the MS IRM system, in terms of increased security provided. Stochastic models are a core part of the process. It was found that the business process is a critical factor in determining document security. Although DRM products improve security, they typically increase the cost to the company and potentially reduce the productivity of staff. Therefore, for a successful deployment of the DRM system, it is recommended that a company evaluate the benefit and cost of DRM systems quantitatively using the procedures described in this document." @default.
• W18583860 created "2016-06-24" @default.
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• W18583860 creator A5036316894 @default.
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• W18583860 date "2013-04-07" @default.
• W18583860 modified "2023-10-03" @default.
• W18583860 title "Cost-benefit analysis of digital rights management products using stochastic models" @default.
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• W18583860 doi "https://doi.org/10.5555/2499604.2499605" @default.
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