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Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Markov Modelling of Fingerprinting Systems for Collision Analysis | Hindawi Publishing Corporation EURASIP Journal on Information Security Volume 2008 Article ID 195238 10 pages doi 10.1155 2008 195238 Research Article Markov Modelling of Fingerprinting Systems for Collision Analysis Neil J. Hurley Felix Balado and Guenole C. M. Silvestre School of Computer Science and Informatics University College Dublin Belfield Dublin 4 Ireland Correspondence should be addressed to Neil J. Hurley neil.hurley@ucd.ie Received 8 May 2007 Revised 19 October 2007 Accepted 3 December 2007 Recommended by S. Voloshynovskiy Multimedia fingerprinting also known as robust or perceptual hashing aims at representing multimedia signals through compact and perceptually significant descriptors hash values . In this paper we examine the probability of collision of a certain general class of robust hashing systems that in its binary alphabet version encompasses a number of existing robust audio hashing algorithms. Our analysis relies on modelling the fingerprint hash symbols by means of Markov chains which is generally realistic due to the hash synchronization properties usually required in multimedia identification. We provide theoretical expressions of performance and show that the use of M-ary alphabets is advantageous with respect to binary alphabets. We show how these general expressions explain the performance of Philips fingerprinting whose probability of collision had only been previously estimated through heuristics. Copyright 2008 Neil J. Hurley et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. 1. INTRODUCTION Multimedia fingerprinting also known as robust or perceptual hashing aims at representing multimedia signals through compact and perceptually significant descriptors hash values . Such descriptors are obtained through a hashing function that maps signals surjectively onto a .
