The evolution of digital technologies allows for efficient manipulation and dissemination of streaming digital content. While providers, distributors and end-users benefit from the evolution to address wider audiences or access improved services, copyright owners are concerned about copyright infringement and illegal proliferation of copyrighted content. Napster triggered off the concern of the industry about the revenue losses entailed by illegal storing, tampering and redistributing copyrighted content on a large scale, piracy. Even thought Napster creators were sued by the recording industry and halted operation, newer programs that can share not only audio, but also video and software have replaced it. Digital Rights Management (DRM) systems are trying to address the problem by enforcing copyrights by means of encrypting the content. Several DRM systems exist for protecting video, such as those used in private-TV broadcasting, DVB, prerecorded DVDs and newer Internetbased ones. Although DRM systems allow the video producer to retain certain control of the content as well as of revenue collection, it has been proven that they are deficient in providing sufficient protection of intellectual rights. The basic reason for this is that any recipient can copy the decoded video and redistribute it without consent of the rights holder. We believe that a DRM solution needs not only to provide copyright enforcement mechanisms but also infringement detection by means of personalization of the content. Personalization can be used to trace back malicious users and hence discourage piracy. Encryption together with watermarking and fingerprinting are technologies needed to prevent piracy and track the proliferation of copyrighted content. Several models address the personalization and dissemination of copyrighted video streams. The most important amongst these models are the One-Stream-To-Each, the One-Stream-To-All, the Active Networks approach and the Selective Encryption and Watermarking model. In the work of this thesis we have identified issues and limitations of these models such as security, scalability, dependency on distribution media and feasibility. In order to address the limitations of the existing systems we contributed the COiN-Video model for the commercial dissemination of copyrighted digital video. The model combines copyright enforcement with personalization of the stream for each user. It addresses the issues identified in existing models, namely scalability, dependency on the distribution media and feasibility. The model is based on dividing the video stream to important/BULK information and the important information to segments that can be watermarked and encrypted individually. Each user receives a unique combination of keys that are needed to decrypt a uniquely identifiable combination of segments. The video stream produced with the combination of the BULK and the personalized segments contains information that can be used to trace back malicious users.