Artificial Intelligence for Detecting Media Piracy

Abstract

Pay TV has evolved from a walled garden, set-top box model to include online services. Although there are numerous operator and consumer benefits that result from this shift, it also opens up tremendous piracy threats that are a nightmare to control. The sheer volume of information being shared in a more open environment means that manpower alone is insufficient to process and detect threats effectively. As artificial intelligence (AI) technology develops in the media space, its application in security must focus on more than closing gaps and locking down assets. Security threats must be spotted and managed faster and more efficiently, before a security instance even occurs. In this paper, we explain how to leverage AI to fight piracy by using content monitoring solutions that search and identify pirated content on the internet. At the core of this technology is an AI-powered computer vision system that identifies the original source of distributed content based on the visual information present in the image (e.g., broadcaster logo). We cover practical issues around building such a system, including its workflow, training, and performance. <disp-quote xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> In this paper, we explain how to leverage AI to fight piracy by using content monitoring solutions that search and identify pirated content on the internet. </disp-quote>