COMPUTER SCIENCE

S E M I N A R

Assured Social Computing

Dr.  Justin Zhan

Department of Computer Science

North Carolina A&T State University

Abstract

Social computing has become more widely known because of its relationship to a number of recent trends. The premise of social computing is that it is possible to design digital systems that support useful functionality by making socially-produced information available to their users. Providing information assurance in social computing is critically important for enabling this functionality. In this talk, I will introduce a number of funded research projects including computational trust framework, secure social networking, secure database search, software security, anomaly detection in dynamic social systems, cloud infrastructure for biomedical computing, and secure social network mining. I will then provide a detailed introduction to the secure social network mining project. Social network mining is a process to extract useful knowledge from large amounts of social network data. To conduct social network mining, we often need to collect data from various resources. However, the data are sometimes distributed and owned by different parties. Privacy and security concerns may prevent the parties from directly sharing the actual values of data and some types of information about the data. How multiple parties can collaboratively conduct social network mining without breaching data privacy and security presents a grand challenge. Theoretical results from the area of secure multi-party computation show that one may provide secure protocols for any multi-party computation with honest majority. However, the general methods are far from efficient and practical for computing complex functions on inputs consisting of large sets of data. I have developed various secure protocols for multiple parties to conduct the desired mining tasks. The solutions are distributed, i.e., there is no centralized, trusted party having access to all the data. In this talk, I will introduce the challenges of secure social network mining and discuss future directions for this research and other related projects.

BIO

Dr. Justin Zhan is the director of iLab (Interdisciplinary Research/Education Laboratory). He has been a faculty member at Carnegie Mellon University, the National Center for the Protection of Financial Infrastructure at South Dakota State, and North Carolina A&T State University. His research interests include Information Assurance, Social Computing, Biomedical Computing and Health Informatics. He is a steering chair of IEEE International Conference on Social Computing (SocialCom), IEEE International Conference on Privacy, Security, Risk and Trust (PASSAT), and IEEE International Conference on BioMedical Computing (BioMedCom). He has been the editor-in-chief of International Journal of Mathematics and Statistics. He is currently an editor-in-chief of International Journal of Privacy, Security and Integrity and International Journal of Social Computing and Cyber-Physical Systems. He has served as a conference general chair, a program chair, a publicity chair, a workshop chair, or a program committee member for over one-hundred international conferences and an editor-in-chief, an editor, an associate editor, a guest editor, an editorial advisory board member, or an editorial board member for about thirty journals. In recent years, he has published more than 130 articles in peer-reviewed journals and conferences and delivered above 30 keynote speeches and invited talks. His research has been sponsored by a number of funding agencies including National Science Foundation, Office of Army Research, Department of Defense, and National Institute of Health.

Tuesday, April 24, 2012

3:30 – 4:30 p.m.

Elva J. Jones Computer Science Building, Room 2200