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8月20日:IT大讲堂---巴渝海外引智专家学术报告通知
2018-08-20 08:45     (浏览次数:)

IT大讲堂---巴渝海外引智专家

学术报告通知

时 间:2018年8月20日(星期一)上午10:00-12:00

地 点:逸夫科技大楼I-412-1

报告人:张渡(Du Zhang)教授,澳门科技大学资讯科技学院院长、重庆科技学院“巴渝海外引智计划”特聘教授

题 目:Smart Network Defense through Perpetual Learning

欢迎广大师生参加。

报告摘要:

Perpetual learning, also known as continuous, life-long, or never-ending learning, an active research direction in machine learning, is concerned with how to develop computing systems that can automatically, consistently and continuously improve their performance at tasks over time. How to safeguard network infrastructure and computing resources for an enterprise in the presence of ever-increasing attacks and exploitations has become a very challenging issue. A critical capability in a network defense system is how to plug the holes in existing security polices and adapt to emerging and new threats and attacks so as to incrementally improve its defensive prowess over time. We believe that perpetual learning offers a viable approach toward building such a smart network defense.

In this talk, we use Snort, a network intrusion detection and prevention system, as the backdrop, and discuss how perpetual learning can be utilized to augment the network defense system with the capability of incremental performance improvement. Learning episodes to engage in incremental performance improvement will be triggered by encountered deficient phenomena. Heuristics specific to the deficient phenomenon will be deployed in each learning episode. The outcome of such a learning episode is a refined or augmented knowledge base that codifies improved security policies. The performance improvements are essentially embodied in security holes being plugged or new threats becoming identifiable. Perpetual learning thus enables a network defense system to become smart over an open-ended sequence of many learning episodes.

报告人简历:

Du Zhangis Professor and Dean of the Faculty of Information Technology, Macau University of Science and Technology, Macau, China. He received his Ph.D. and M.S. degrees, both in computer science, from the University of Illinois and Nanjing University, China, respectively. Previously he was a Professor and Chair of the Computer Science Department at California State University, Sacramento. He has research affiliations with numerous universities in the USA, UK, France, Hong Kong, Czech Republic, and Mexico. Professor Zhang's current research interests include machine learning (inconsistency-induced perpetual learning), knowledge-based systems, big data analytics, and software engineering. He has over 200 publications in these and other areas. He has served in various roles on numerous international conferences, and is editor or editorial board member for several journals in the areas of artificial intelligence, software engineering and knowledge engineering, big data, and applied mathematics.

主办单位:智能技术与工程学院 电气工程学院

发布单位:科研处

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