Multimedia Security and Forensics

in
PhD Seminar Course on

Multimedia Security and Forensics

Cagliari, May, 17-24, 2011
Instructor: Prof. Chang-Tsun Li - University of Warwick, UK
Chang-Tsun Li received the B.E. degree in electrical engineering from Chung-Cheng Institute of Technology (CCIT), National Defense University, Taiwan,  the M.S. degree in computer science from U. S. Naval Postgraduate School, USA, and the Ph.D. degree in computer science from the University of Warwick, UK, in 1998.
His research interests include digital forensics, multimedia security, bioinformatics, computer vision, image processing, pattern recognition, evolutionary computation, machine learning and content-based image retrieval. Dr Li has published more than 100 articles in journals, books and conference proceedings.
He is currently Associate Professor of the Department of Computer Science at the University of Warwick, UK. Before taking up his current appointment at Warwick, he was Associate Professor of the Department of Electrical Engineering at CCIT during 1998-2002 and Visiting Professor of the Department of Computer Science at U.S. Naval Postgraduate School in the second half of 2001.
He is also the coordinator of an EU FP7 project entitled Digital Image and Video Forensics funded through the Marie Curie Industry-Academia Partnerships and Pathways (IAPP) from June 2010 to May 2014. He is currently involved in three major multidisciplinary research projects funded by the EU and British funding agencies.
Dr. Li is also the Editor-in-Chief of the International Journal of Digital Crime and Forensics. He has involved in the organisation of a number of international conferences and workshops and also served as member of the international program committees for several international conferences.
Duration: 8 hours
Schedule:
  • Tuesday May 17th 10.00 – 12 – Topics 1-2. Slides.
  • Thursday May 19th 10.00 – 12 – Topics 3-4. Slides.
  • Friday May 20th 10.00 – 12 – Topics 5-6. Slides.
  • Tuesday May 24th 10.00 – 12 – Topics 7-8. Slides.
Venue: Room G - Faculty of Engineering
Topics: Topic 1: Robust digital watermarking
After an introduction of different types of digital watermarking schemes and their applications in multimedia security and forensics at the beginning of this topic, I will present robust watermarking and its application in multimedia copyright protection, including owner identification, transaction tracking / fingerprinting and copy control.

Topic 2: Fragile and semi-fragile digital watermarking
This topic deals with the use of fragile watermarking in multimedia authentication and integrity verification. Fragile and semi-fragile schemes are expected to be sensitive to manipulation, i.e., if manipulated, the watermark embedded in the host media should be destroyed such that the manipulated media will not pass the authentication.

Topic 3. Properties and security of digital watermarking
This topic is deliberately postponed until example schemes have been introduced in the previous two topics. Properties, such as embedding effectiveness, imperceptibility, data payload, need to be considered when designing watermarking systems will presented.  Security requirements of various watermarking schemes will also be covered in this topic.

Topic 4. Steganography and Steganalysis
Steganography is the technique of hiding data in the plain media while maintaining the fidelity of the stego-media (i.e., the media with hidden data) in order to serve the purpose of covert communication. On the other hand, steganalysis is the competing technique for detecting the presence of hidden data in multimedia.

Topic 5. Source device identification based on device signatures extracted from images
Topic 1 – 4 is about using extrinsic information (i.e., watermark or secret data artificially embedded in the host media) for providing multimedia protection and authentication. However, those techniques are not applicable to unwatermarked multimedia. Topic 5 to 8 cover multimedia forensic techniques that rely on intrinsic information in the content (i.e., the information that is part of the original content). Topic 5 deals with the use of minute information (device signatures) left by the imaging devices in the images for identifying the source devices. Various types of device signatures will be introduced.

Topic 6. Source device identification based on enhanced sensor pattern noise
Topic 6 is also about source device identification. However, it targets specifically the identification techniques that rely on Sensor Pattern Noise (SPN) left in the images by the semiconductor sensor of the imaging devices. SPN is the unique noisy signal due to the imperfection during the manufacturing process of semiconductor wafers. An enhancer of SPN recently developed by the speaker will be presented.

Topic 7. Unsupervised pattern classification
Topic 7 is intended to pave the way for the presentation of topic 8. A generic unsupervised pattern classifier using random fields will be introduced. This generic classifier requires neither a training phase nor the user’s specification of the number of classes / clusters and the characteristics of the features / patterns (e.g., centroid of each class).  Therefore, it can be adapted for various applications easily.

Topic 8. Unsupervised image clustering based on enhanced sensor pattern noise
There are circumstances where a forensic investigator has a large set of images taken by an unknown number of unknown cameras and wants to cluster those images into a number of groups, each including the images taken by the same camera, in order to narrow down the investigation. A blind image clustering method based on the enhanced sensor pattern noise will be introduced in this topic. The core of this image clustering technique is the generic classifier introduced in Topic 7.
Organizer: Prof. Gian Luca Marcialis
Dep. of Electrical and Electronic Engineering
University of Cagliari, Italy
Email: marcialis(at)diee(dot)unica(dot)it