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美国蒙莫斯大学Mohammad S. Obaidat教授应高等智能与网络服务111引智基地的邀请，将于11月27日来北邮作学术报告。欢迎有兴趣的师生踊跃参与。讲座题目：A Biometric Methodology for Risk-Based Authentication in Web Environments 主讲人：Mohammad S. Obaidat教授（IEEE Fellow, SCS Fellow, 美国蒙莫斯大学) 主持人：纪红教授时间：2012年11月27日（星期二）下午16:00-17:30 地点：教3-811报告厅此讲座为前沿课题讲座，欢迎全校师生踊跃参加。报告人简介： Professor Mohammad S. Obaidat (Fellow of IEEE and Fellow of SCS) is an internationally well-known academic/researcher/ scientist. His research interests are: wireless networks, telecommunications and networking systems, security of network, green ICT, information and computer systems, performance evaluation of computer systems, and so on. He has published over 10 books and over 550 refereed technical articles. Mohammad is the Editor-in-Chief of 3 scholarly journals and is also an editor, advisory editor of numerous international journals and transactions. He has chaired numerous international conferences and given numerous keynote speeches all over the world. Until very recently, Prof. Obaidat served as the President of the Society for Modeling and Simulation International, SCS. He served as the Advisor to the President of Philadelphia University for Research, Development and IT. He also served as the Chair of the Department of Computer Science and Software Engineering and as the Director of Graduate Program at Monmouth University, NJ. Furthermore, he is an ACM and SCS Distinguished Lecturer/speaker and served as an IEEE Distinguished Speaker. 报告摘要 Existing risk-based authentication systems rely on basic web communication information such as the source IP address or the velocity of transactions performed by a specific account, or originating from a certain IP address. Such information can easily be spoofed. In this talk, we propose a new online biometric risk-based authentication system that provides more robust user identity information by combining mouse dynamics and keystroke dynamics biometrics in a multimodal framework. Experimental evaluation of our proposed model with 24 participants yields an Equal Error Rate of 8.21%, which is promising considering that we are dealing with free text and free mouse movements, and the fact that many web sessions tend to be very short. Moreover, we believe this performance is adequate for reactive risk-based authentication, where the goal is not to prevent the user from using the system, but rather to identify malicious sessions and trigger appropriate risk mitigation measures. 校学术委员会高等智能与网络服务111引智基地国际合作与交流处 2012/11/23

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