2009 International Conference on

                    Computational Intelligence and Security

                                                                                                    Beijing, China December 11-14,2009

      

Zongben Xu

Short Biography for Dr. Xu

Dr.Xu received his MS degree in Mathematics in 1981 and PhD degree in applied Mathematics in 1987 from Xi'an Jiaotong University, China. In 1998, he was a post-doctoral researcher in the Department of Mathematics, The University of Strathclyde (UK), He worked as a research fellow in the Department of Computer Science and Engineering from 1992 to 1994, and 1996 to 1997, at The Chinese University of Hong Kong; a visiting professor in the University of Essex (UK) in 2001, and Napoli University (Italy) in 2002. He has been with the Faculty of Science and Institute for Information and System Sciences at Xi`an Jiaotong University since 1982, where he was promoted to associate professor in 1987 and full professor in 1991, and now serves as professor of Mathematics and Computer Sciences, and vice president of Xi'an Jiaotong University. In 2007, he was appointed as a Chief Scientist of National Basic Research Program of China (973 Project).
Professor Xu currently makes several important services for government and professional societies, including Consultant Expert for National (973) Program in Key Basic Science Research and Development (Information group), Ministry of Science and Technology of China; Evaluation Committee Member for Mathematics Degree, Academic Degree Commission of the Chinese Council; Committee Member in Scientific Committee of Education Ministry of China (Mathematics and Physics Group); Vice-Director of the Teaching Guidance Committee for Mathematics and Statistics Majors, the Education Ministry of China; Director of the Teaching Guidance Committee for Mathematics Education, the Education Ministry of China; Member in the Expert Evaluation Committee for Natural Science Foundation of China (Computer Science Group), The National Committee for Natural Science Foundation of China; Vice-president of Computational Intelligence Society of China; Editor-in-chief of the Textbooks on Information and Computational Sciences, Higher Education Press of China; Co-editor of nine national and international journals.
Professor Xu has published over 150 academic papers on non-linear functional analysis, optimization techniques, neural networks, evolutionary computation, and data mining algorithms, most of which are in international journals. His current research interests include non-linear analysis, machine learning and computational intelligence. Dr. Xu holds the title "Owner of Chinese PhD Degree Having Outstanding Achievements" awarded by the Chinese State Education Commission (CSEC) and the Academic Degree Commission of the Chinese Council in 1991. He is owner of the National Natural Science Award of China in 2007，and winner of CSIAM Su Buchin Applied Mathematics Prize in 2008.                    

                     Vision Inspired Data Modeling
                                           
As common basis of information technologies, data modeling has become one of the main forms of mathematical application. Its aim mainly is to reveal useful information from data (structure, pattern, rule, relations, etc.). Traditional data modeling, such as statistics and artificial intelligence methods, bases mainly upon the data structure as well as the physical principle to produce the data. In the past years we have developed the principle and methodology of data modeling based on simulating cognition principles. In this talk we review the recent work done by my group on data mining (DM) technologies inspired from visual recognition principle. The main topics will include: (i) the scale space based DM technologies via simulating ideal retina property, (ii) the receptive field mechanism and gestalt psychology based DM methods deduced from mimicking retina and preliminary cortex principle, and (iii) the neural coding based DM technologies from simulating nonlinear coding mechanism in visual system. In each topic, we explain our new idea, formulate the algorithms and compare the new technologies with the existing ones. We show that such cognition based DM methods very often lead to state-of-the-art DM techniques.

 Witold Pedrycz

Professor and Chair Canada Research Chair IEEE Fellow

Short Biography for Dr Pedrycz

Witold Pedrycz is a Professor and Canada Research Chair (CRC - Computational Intelligence) in the Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada and Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland. He main research pursuits involve Computational Intelligence, Granular Computing, fuzzy modeling, knowledge discovery and data mining, fuzzy control including fuzzy controllers, pattern recognition, knowledge-based neural networks, relational computation, and Software Engineering. He has published numerous papers in this area. He is also an author of 14 research monographs covering various aspects of Computational Intelligence, data mining, fuzzy sets, and Software Engineering. Witold Pedrycz has been a member of numerous program committees of IEEE conferences in the area of fuzzy sets and Computational Intelligence.
Dr. Pedrycz is intensively involved in editorial activities. He is an Editor-in-Chief of Information Sciences and Editor-in-Chief of IEEE Transactions on Systems, Man, and Cybernetics - part A. He currently serves as an Associate Editor of IEEE Transactions on Fuzzy Systems, and a number of other international journals. He has edited a number of volumes; the most recent entitled “Handbook of Granular Computing” (J. Wiley, 2008). In 2007 he received a prestigious Norbert Wiener award from the IEEE Systems, Man, and Cybernetics Council. He is a recipient of the IEEE Canada Computer Engineering Medal 2008.

           Human centricity of Granular Computing- a design of conceptual and algorithmic                                           framework of Computational Intelligence

                                                                 
In Computational Intelligence (CI), we are faced with new challenges and opportunities that can translate to the enhancements of the ways in which its underlying technologies and fuzzy sets, in particular, become utilized. More often than before we encounter systems that are distributed and hierarchical in their nature, in which there is a significant level of knowledge generation and knowledge sharing. As a matter of fact, knowledge generation is inherently implied by the mechanisms of collaboration and knowledge sharing being realized between participating systems. Along with the need for a more effective interaction, we are also faced with associated security and privacy requirements. The aspects of distributed intelligence and agent systems stress the facet of human centricity and human–centric computing (HC2). In numerous ways of forming efficient conceptual and algorithmic vehicles of human-system interaction, fuzzy sets and Granular Computing, in general, have been playing an important role in the HC2 domain. The feature of human centricity of Granular Computing and fuzzy set-based constructs is the underlying leitmotiv of our investigations. More specifically, we concentrate on some new directions of knowledge elicitation and knowledge quantification realized in the setting of fuzzy sets.
With this regard, we elaborate on an idea of knowledge-based clustering, which aims at the seamless realization of the data-expertise design of information granules. We emphasize the need for this unified treatment in the context of knowledge sharing where fuzzy sets are developed not only on the basis of numeric evidence available locally but in their construction we also actively engage the domain knowledge being shared by others. It is also emphasized that collaboration and reconciliation of locally available knowledge give rise to the concept of higher type fuzzy sets along with the principle of justifiable granularity supporting their construction. This principle helps capture the diversity of numeric entities and encapsulate them in the form of information granules where the level of granularity is adjusted to quantify the level of existing diversity. In the setting of the formation of information granules, we also elaborate on the associated issue of information security. The other interesting direction enhancing human centricity of computing with fuzzy sets, deals with non-numeric characterization of information granules (fuzzy sets). We discuss a suite of algorithms facilitating a qualitative assessment of fuzzy sets, formulate a series of optimization tasks guided by well-formulated performance indexes and discuss the essence of the resulting solutions. We show how the obtained results allow us to view constructs of Computational Intelligence in a broader context of HC2 architectures and introduce a concept of linguistic equivalence, linguistic stability and other qualitative descriptors. We also revisit a plethora of logic operators available in the theory of fuzzy sets vis-à-vis their qualitative interpretation.
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C. L. Philip Chen    

 Professor and Chair Fellow,IEEE

Short Biography for Dr. C. L. Philip Chen

Dr. Chen received his M.S. degree from the University of Michigan, Ann Arbor, Michigan, in 1985, and Ph.D. degree from Purdue University, West Lafayette, Indiana, in 1988. He was a visiting assistant professor at the School of Engineering and Technology, Purdue University, Indianapolis, Indiana, 1988-1989. Since September 1989, he has been with the Computer Science and Engineering Department, Wright State University, Dayton, Ohio, as an assistant, an associate, and a full professor. Since September 2002, he has joined, as a full Professor, the Department of Electrical and Computer Engineering, The University of Texas at San Antonio, where he has been the Associate Dean for Research and Graduate Studies and Interim Chair. Currently he is the Department Chair.

Dr. Chen has been a visiting research scientist, at the Materials Directorate, Wright Laboratory, Wright-Patterson Air Force Base. He has been a senior research fellow sponsored by the National Research Council, National Academy of Sciences. He was on sabbatical leave to Purdue University and Case Western Reserve University from Fall 1996 to Fall 1997, a visiting professor to Beijing Normal University and XinJiang University, Summer 2000, Beijing Institute of Technology, 2006, a chair professor of National Chung Hsing University, 2009-2011. He also has been a research faculty fellow for Wright-Patterson Air Force Base and NASA Glenn Research Center for several years. His research interests and projects, supported by the NSF, Air Force Office Scientific Research and the U.S. Air Force, Office of Naval Research, NASA, and State of Ohio, include computer networking, neural networks, fuzzy-neural systems, intelligent systems, robotics, and CAD/CAM. His current research areas include design computational intelligent systems, networking, and video data indexing, retrieval, and communications; and a research project funded by the NASA Glenn Research Center on data mining on aircraft flight and maintenance data, aircraft engine life prediction, life extending control, diagnosis and prognosis, and health monitoring. As a result of his research contribution and academic recognition, he was elected to a Fellow of the IEEE.

Dr. Chen has been involving in professional service for twenty years. He has served as a member of organizing committee for many IEEE conferences under different capacities, including IEEE International Conference on Robotics and Automation, IEEE WCCI, IEEE Int'l Conf. on Intelligent Robotics and Systems (IROS), IEEE Int'l Conf. on SMC, IEEE Int'l Conf. on System of Systems. Notably, he also has been a Conference Co-Chair of the International Conference on Artificial Neural Networks in Engineering (ANNIE), 1995 and 1996; the Program Co-Chairs of 2006 IEEE/SMC Int'l Conference on System of Systems Engineering (SoSE); General Co-Chair of 2008 IEEE Int'l Conference on Secure Systems Integration and Reliability Improvement (SSIRI 2008); and General Chair of 2009 IEEE Int'l Conf. on Systems, Man, and Cybernetics. Currently, he is the Vice President on Technical Activities in Systems Science and Engineering of IEEE SMC Society, where he has been a member of Board of Governors, the Treasurer; and serves as a Distinguished Lecturer, an Associate Editor of IEEE Transactions on SMC-C and IEEE Systems Journal. He is the founding faculty advisor of the IEEE Computer Society Student Chapter while at Wright State University and the founding Chair of IEEE SMCS Central Texas Section; founding co-chairs of three SMCS Technical Committees (SoS, Enterprise Information Systems, and Information Assurance). With this recognition, he received Outstanding Contribution Award from IEEE SMCS in 2008. Dr. Chen is a member of Tau Beta Pi and Eta Kappa Nu honor societies and has been the faculty advisor for Tau Beta Pi Engineering honor society. In addition, he is an ABET (Accreditation Board of Engineering and Technology Education) program evaluator for Computer Engineering, Electrical Engineering, and Software Engineering programs.

               Multimedia Information Security: An Overview of Research and Challenges

                                                                         
Digital multimedia content, can be created, edited, distributed, shared, and stored with convenience at a very low cost over the mobile and ad hoc nature of today's various networks. As a result, multimedia security and digital authentication, transmission and detection of sensitive information via communication systems have become a very important research subject recently. Encryption and data hiding are two most popular areas in multimedia security research. This talk will focus on data hiding techniques, especially, steganography techniques.
Steganography is the hiding of a message within another message so that the presence of the hidden message is indiscernible. Practically, it is the art of secret communication. Digital data can be hidden in pictures, videos, music, text, binary files, or source code. The key concept behind steganography is that the message to be transmitted is not visible to the informal eye or ears. In fact, people who are not intended to be the recipients of the message should not even suspect that a hidden message exists. After September 11, steganography has received enormous attention in industry and in academia. Recently USA Today reported that Bin Laden was using information hiding to disguise his communications.

One the hand, the purpose of steganalysis is to discover the presence of hidden messages in digital media. Steganography and steganalysis have not been completely examined in detail by the scientific community outside the military. It is a relatively new and fast growing field. Over 90% of all the open publications have appeared in the past seven years. This area now has become a multimillion-dollar research market, and closely related to the security of our nation.
In this talk, we summarize stegano research accomplishments during the past few years and propose a number of directions for future research.

Note: The presented work is based on the result from Dr. Sos Agaian and Dr. Philip Chen funded by Center of Information Assurance and Security, U.S. the Air Force Information Warfare Center.
Personal Home Page: http://engineering.utsa.edu/~pchen/pchen1.html
Email: Philip.Chen@utsa.edu