Keynote lectures are plenary sessions which are scheduled for taking about 45 minutes + 10 minutes for questions.
 
       
- Ingemar Cox, University College London, United Kingdom
Keynote Lecture 1
Watermarking, Steganography and Content Forensics
 
       
  Ingemar Cox,
University College London, United Kingdom
       
Brief Bio:
Ingemar J. Cox is currently Professor and BT Chair of Communications in the Departments of Computer Science, and Electronic and Electrical Engineering at University College London and Director of UCL's Adastral Park Postgraduate Campus. He is currently a holder of a Royal Society Wolfson Fellowship. He received his B.Sc. from University College London and Ph.D. from Oxford University. He was a member of the Technical Staff at AT\&T Bell Labs at Murray Hill from 1984 until 1989 where his research interests were focused on mobile robots. In 1989 he joined NEC Research Institute in Princeton, NJ as a senior research scientist in the computer science division. At NEC, his research shifted to problems in computer vision and he was responsible for creating the computer vision group at NECI. He has worked on problems to do with stereo and motion correspondence and multimedia issues of image database retrieval and watermarking. In 1999, he was awarded the IEEE Signal Processing Society Best Paper Award (Image and Multidimensional Signal Processing Area) for a paper he co-authored on watermarking. From 1997-1999, he served as Chief Technical Officer of Signafy, Inc, a subsidiary of NEC responsible for the commercialization of watermarking. Between 1996 and 1999, he led the design of NEC's watermarking proposal for DVD video disks and later colloborated with IBM in developing the technology behind the joint "Galaxy" proposal supported by Hitachi, IBM, NEC, Pioneer and Sony. In 1999, he returned to NEC Research Institute as a Research Fellow. He is a Fellow of the IEEE, the IET (formerly IEE), and the British Computer Society. He is a member of the UK Computing Research Committee. He was founding co-editor in chief of the IEE Proc. on Information Security and is an associate editor of the IEEE Trans. on Information Forensics and Security. He is co-author of a book entitled "Digital Watermarking" and its second edition "Digital Watermarking and Steganography", and the co-editor of two books, `Autonomous Robots Vehicles' and `Partitioning Data Sets: With Applications to Psychology, Computer Vision and Target Tracking'.
 
Abstract:
Electronic watermarking is about 60 years old. However it was not until the beginning of the early 1990's that watermarking received widespread interest, due to concerns about piracy of digital content. In the subsequent decade, very significant progress has been made both in our theoretical understanding of digital watermarking and in its applications. This progress is described here. Steganography has a much longer history, dating back to at least the time of the ancient Greeks. While Shannon dismissed steganography as "{primarily a psychological problem}", the last decade has seen the application of information theory to steganography. Terrorist events at the beginning of the 21st century motivated further attention and very interesting results have been described. At first sight, digital watermarking and steganography would appear to share the same goals. However, while both seek to hide information within other information or content, there are very significant differences in the constraints that must be satisfied. The similarities and differences between digital watermarking and steganography are highlighted here.
Steganography spawns steganalysis, the art and science of detecting the presence of a steganographic message hidden in innocuous content. Recent research views steganalysis as a binary classification problem; is a hidden message present or absent? Classification is based on testing for statistical anomalies in features derived from the content. Content forensics shares similarities with steganalysis. At the simplest level, content forensics is often asked whether, for example, an image is authentic or has been tampered with. This problem can also be viewed as a binary classification problem and similar techniques can be applied. We will review recent work in content forensics and steganalysis, and discuss the limitations of both.