TY - CONF T1 - A decision theoretic framework for analyzing binary hash-based content identification systems T2 - Proceedings of the 8th ACM workshop on Digital rights management Y1 - 2008 A1 - Varna,Avinash L. A1 - Swaminathan,Ashwin A1 - M. Wu KW - content fingerprinting KW - content identification KW - decision theory AB - Content identification has many applications, ranging from preventing illegal sharing of copyrighted content on video sharing websites, to automatic identification and tagging of content. Several content identification techniques based on watermarking or robust hashes have been proposed in the literature, but they have mostly been evaluated through experiments. This paper analyzes binary hash-based content identification schemes under a decision theoretic framework and presents a lower bound on the length of the hash required to correctly identify multimedia content that may have undergone modifications. A practical scheme for content identification is evaluated under the proposed framework. The results obtained through experiments agree very well with the performance suggested by the theoretical analysis. JA - Proceedings of the 8th ACM workshop on Digital rights management T3 - DRM '08 PB - ACM CY - New York, NY, USA SN - 978-1-60558-290-0 UR - http://doi.acm.org/10.1145/1456520.1456532 M3 - 10.1145/1456520.1456532 ER -