1st International Conference on Contemporary Computing and Informatics
Data Hiding: Optimization Framework, Random Gain Attack and Compressed Sensing

With the advancement in digital techniques, high speed computing and wireless networks, digital media now can be disseminated worldwide almost in error free form, of course, with a threat of copyright infringement, authentication and security for the multimedia data. One popular technique, namely Data Hiding in general form (steganography and watermarking as specialized forms) had been proposed over the last one and half decade as potential solution to media protection problem involving tools, techniques and concept from different diverse disciplines, namely digital communication, signal processing, set theory, soft computing, multimedia coding, information theory, cryptography, computer science, game theory etc. Although developed initially to meet the purpose of copyright protection, data authentication, content integrity verification etc., this technique has largely been tested in due times for plurality of applications, ranging from security in communication, broadcast monitoring, medical imaging, fingerprinting and data indexing, quality assessment and error concealment in multimedia communication to a few newer promises like digital forensic application, media protection at low measurement signal/image acquisition (compressed sensing) and possible integration in physical layer security in wireless networks.

Literature is quite rich for embedding techniques, attack modeling and decoder design. However, challenges and scopes for newer applications demand new solutions in an optimization framework involving intelligent computing; incorporating more generalized modeling of attack channel in stochastic nature and improved decoder performance at low signal (signature) power. Existing literature look design of data hiding technique as an optimization problem from min-max perspective i.e. minimizing perceptual distortion and maximizing the watermark decoding in additive Gaussian attack channel. However, the optimization framework changes in presence of a random gain (fading-like) attack. Fading-like attack gain in image and video data may occur due to many reasons, for example, the display and the printing device characteristics, intelligent collusion operation in digital rights management, multimedia transcoding, data transmission in radio mobile channel, during scanning process on images as light may not be uniformly distributed on the paper, skewed histogram of an image, reconstruction of image/video signals from compressed sensing or compressive sampling measurement space and many others.

This tutorial first gives a general introduction in data hiding, its multidisciplinary research flavor, integration with contemporary security schemes, two popular classes of data hiding strategies: Spread Spectrum (SS) and quantization index modulation (QIM) and various applications of data hiding. The discussion is then extended in optimization framework that maximizes watermark robustness against AWGN using SS scheme.

The second part of the lecture introduces random attack gain, relevancy, justification and modeling followed by optimized data hiding scheme in presence of such attack; discussion on application specific cases, for example error concealment in radio mobile channel and intelligent collusion in DRM. Several soft computing tools, namely fuzzy logic (FL), Genetic algorithms (GAs) and artificial neural networks (ANN) how can be used as individual one and in integrated form as optimization tools in system design using digital communication principles of SS, CDMA, MC-CDMA, multiuser detection etc. and signal processing tools like wavelets and its variants.

Last part of the talk will introduce data protection at compressed sensing (CS) paradigm, an emerging technique for image/video acquisition and reconstruction at low measurement space (much below the Nyquist sampling rate) exploiting the computation power at later stage. This is essential as in many practical situations, particularly in medical imaging, sensing process may be slow so that one can measure only the objects a few times or there may be the limited number of sensors used or measurements may be extremely expensive. Challenge here lies how to protect such images right at the time of acquisition or capturing, of course, at low SNR.

The topic of tutorial expects to attract research community of diverse disciplines to design integrated system in data hiding using various bio-inspired computing, optimization problem solving using these tools sets as well as use of classical convex problem solution, several norms, like l0, l1 or l2 minimization problems in CS, recursive (or iterative) filtering techniques for image reconstruction using Robinns-Monro stochastic approximation, orthogonal basis pursuit, GLRT for parameter estimation, computational forensic problems, physical layer security etc.

Speaker:Dr. Santi P.Maity, Professor, Dept. of Information Tech., IIEST, Shibpur, Howrah

Dr. Santi P. Maity received his B. E. degree in Electronics and Communication Engineering of National Institute of Technology, Durgapur and M. Tech in Microwaves with specialization in digital communication, from the University of Burdwan, West Bengal, India in 1993 and 1997, respectively. He received his Ph. D degree in Engineering (Computer Sc. and Technology) from Bengal Engineering and Science University, Shibpur, India in 2008 in association with Machine Intelligence Unit, Indian Statistical Institute, Kolkata. He received couple of post-doctoral research positions in different universities, namely Nanyang Technological University, Singapore, Laboratoire des Signaux et Systems, France and University of Vigo, Spain. He did his post-doctoral for SIX months duration twice (January 2009 to July 2009 and February 2011 to July 2011) in the “Laboratoire des Signaux et Systems (CNRS-Supelec-Universite Paris-Sud 11)” in France. He is at present working as Professor since 1st November, 2012 in Indian Institute of Engineering Science and Technology, Shibpur, India (Formerly known as Bengal Engineering and Science University, Shibpur). He was Head of the department of Information Technology in IIEST, Shibpur since February, 2012 to 31st January, 2014. His research interests include Digital Watermarking, Secret Sharing, Medical Image Reconstruction at Compressed Sensing and Segmentation, Extraction and Analysis of Blood Vessels on Retinal Images, MC-CDMA, Cognitive Radio Networks, Cooperative spectral sensing and compressive sampling. He has published about 150 research papers in International journals, conference proceedings, in edited volumes etc. He has completed Govt. of India sponsored project as Principal Investigator, supervised several Master and Ph. D students, and delivered many lectures in National Seminars, Workshops, Faculty Development Programs and International Conferences.


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