The 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications (IEEE TrustCom-18)
August 1st-3rd, 2018, New York, USA.


Keynote Speakers


Prof. Witold Pedrycz
Canada Research Chair,
IEEE Fellow,
Professional Engineer,
Department of Electrical and Computer Engineering,
University of Alberta

Bio: Witold Pedrycz (IEEE Fellow, 1998) is Professor and Canada Research Chair (CRC) in Computational Intelligence in the Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada. He is also with the Systems Research Institute of the Polish Academy of Sciences, Warsaw, Poland. In 2009 Dr. Pedrycz was elected a foreign member of the Polish Academy of Sciences. In 2012 he was elected a Fellow of the Royal Society of Canada. Witold Pedrycz has been a member of numerous program committees of IEEE conferences in the area of fuzzy sets and neurocomputing. In 2007 he received a prestigious Norbert Wiener award from the IEEE Systems, Man, and Cybernetics Society. He is a recipient of the IEEE Canada Computer Engineering Medal, a Cajastur Prize for Soft Computing from the European Centre for Soft Computing, a Killam Prize, and a Fuzzy Pioneer Award from the IEEE Computational Intelligence Society.

His main research directions involve Computational Intelligence, fuzzy modeling and Granular Computing, knowledge discovery and data science, fuzzy control, pattern recognition, knowledge-based neural networks, relational computing, and Software Engineering. He has published numerous papers in this area. He is also an author of 16 research monographs and edited volumes covering various aspects of Computational Intelligence, data mining, and Software Engineering.

Dr. Pedrycz is vigorously involved in editorial activities. He is an Editor-in-Chief of Information Sciences, Editor-in-Chief of WIREs Data Mining and Knowledge Discovery (Wiley), and Int. J. of Granular Computing (Springer). He serves on an Advisory Board of IEEE Transactions on Fuzzy Systems and is a member of a number of editorial boards of international journals.

Topic: User-Centricity in Big Data Problems

Time: TBD.

Abstract: Big Data technology offers enormous potential and becomes a necessity in the era of omnipresent data. To unleash this potential, along with new paradigms, some existing principles need to be thoroughly revisited. As never seen so vividly before, the user assumes a central position in facilitating pursuits of big data by formulating some initial direction of the overall analysis and subsequently evaluating the value and actionability of the obtained findings. This entails that when considering the well-known list of Vs present in big data, the properties of value and veracity assume a pivotal role. The feature of user–centricity deserves a thorough discussion, especially in terms of defining the concept itself and identifying its multiway nature embracing transparency, interpretability, comprehension, and scalability.

The notions of abstraction and levels of abstraction, which are inherently involved in data analytics, can be conveniently realized in the form of information granules. The facet of abstraction (information granularity) makes the problems more manageable by positioning various constructs and processes at the level of a limited number of information granules. The abstraction mechanism is completed in the data space as well as feature (attribute) space resulting in granular data and granular features. Information granules can be sought as an outcome of realization of a generalized sampling mechanism.

In the talk, discussed are main ways of building information granules along with pertinent mechanisms of characterization of their quality and abilities to represent original data (reconstruction aspects). The tradeoffs present among the specificity of information granules, their abilities to describe the original data and related computing overhead are identified and quantified. Building a variety of models (predictors, classifiers, linkage analyzers, etc.) carried out in the presence of information granules (granular data) instead of original data comes with intriguing questions about the relevance of findings discovered at this particular level of abstraction, their comprehension and stability (robustness).





Prof. Jie Wu

IEEE Fellow,
Director of International Affairs,
College of Science and Technology,
Director of Center for Networked Computing (CNC),
Laura H. Carnell Professor, Department of Computer and Information Sciences,
Temple University

Bio: Jie Wu is a Chinese computer scientist. He is the Associate Vice Provost for International Affairs and Director for Center for Networked Computing at Temple University. He also serves as the Laura H. Carnell professor in the Department of Computer and Information Sciences. He served as Program Director of Networking Technology and Systems (NeTS) at the National Science Foundation from 2006 to 2008. Jie Wu is noted for his research in routing for wired and wireless networks. His main technical contributions include fault-tolerant routing in hypercube-based multiprocessors, local construction of connected dominating set and its applications in mobile ad hoc networks, and efficient routing in delay tolerant networks, including social contact networks.

He served as the General Chair of IEEE ICDCS 2013, IEEE IPDPS 2008, and IEEE MASS 2006 and the Program Chair of CCF CNCC 2013, IEEE INFOCOM 2011, and IEEE MASS 2004. He is a Fellow of IEEE and serves on the editorial board for a number of journals, including IEEE Transactions on Computers (TC), IEEE Transactions on Services Computing (TSC), and Journal of Parallel and Distributed Computing (JPDC). He received 2011 China Computer Federation (CCF) Overseas Outstanding Achievements Award. He was a Fulbright Senior Specialist. He was also an IEEE Distinguished Visitor and an ACM Distinguished Speaker and is currently a CCF Distinguished Speaker.

Topic: On Authenticated Query Processing via Untrusted Cloud Service Providers

Time: TBD.

Abstract: In data publishing, the owner usually delegates the role of query processing to a third party publisher, such as cloud service providers (CSPs). CSPs are untrusted as they can fabricate query results, provide incomplete ones, or do both. We need to develop sound while efficient mechanisms to ensure completeness and authenticity of query results from a CSP. Validation can be done in one of the two ways: a small number of digests distributed periodically from the owner to the user, or, embedded verification objects stored in CSP, together with data, by the owner and passed to the user as part of query results. We consider a set of special queries which return a partition of data, based on the notion of logical or physical vicinity. These queries include range, top-k, skyline, and kNN (k-nearest-neighbor). Verification objects, through digital signatures and hash functions, authenticate and compress all partitioned data through chains and trees. The design of verification objects also depends on the query type and the structure of data, which may be multi-dimensional. This talk discusses several efficient designs of verification objects. The focus is on a special verification object based on composite linear certified chains. Such chains can be efficiently applied to multi-dimensional data applications where data change relatively frequently, and as a result, certified chains need to be quickly updated as well.




Prof. Xiaodong Wang

IEEE Fellow,
Columbia University, USA

Bio: Professor Xiaodong Wang was an assistant professor from July 1998 to December 2001 at the Department of Electrical Engineering at Texas A&M University. In January 2002, he joined the Department of Electrical Engineering at Columbia University as an assistant professor. Dr. Wang's research interests fall in the general areas of computing, signal processing, and communications. He has worked and published extensively in the areas of wireless communications, statistical signal processing, parallel and distributed computing, nanoelectronics, and quantum computing. Dr. Wang has received the 1999 NSF CAREER Award. He has also received the 2001 IEEE Communications Society and Information Theory Society Joint Paper Award.

Topic: TBD

Time: TBD.

Abstract: TBD