Efficient Design of Interpretation of REL License Using Expert Systems

other flexible rights language is often a difficult task, due to the flexibility of the language and the lack of formal semantics. An efficient way to manage this complexity is to translate the license into a set of clearly defined knowledge predicate, and process this knowledge via inference rules using an expert system. This improves computational efficiency and allows authorization request to be verified against a large number of licenses without dependency issues. I. INTRODUCTION ith the increased proliferation of digital information and media, especially in the field of on-line sales of digital media, brings about a change in the business model of sales of information. In order to support more creative business models, which was not possible before, a method in which rights and transactions can be described with greater flexibility is required. Through an intensive standardization process, the Rights Expression Language (REL) [1] from MPEG-21 [2], strives to define a flexible and extensible description language, which can be used to describe generic rights model between different parties. Digital Rights Management (DRM) systems use rights expression languages together with cryptographic algorithms to protect and manage digital contents. A more flexible or expressive rights expression language, which can closely model the rights exchange between consumers and content providers, would brings about greater convenience for users and improve the user experience. This would be crucial to the acceptance of DRM systems, as DRM becomes a convenient means of exchange of digital information, without placing unnecessary restrictions on the user. However, with the increased flexibility, brings about greater complexity in analyzing and interpreting licenses. Thus, this paper proposes an efficient design for a license interpretation engine, based on an expert system architecture. Part II of this paper describes the implementation of this expert system based license interpreter. Section A shows the