6月11日学术报告（张锐美国特拉华大学）

6月11日学术报告（张锐美国特拉华大学）

类别：未知发布人：admin 浏览次数：次发布时间：2018-06-11 13:20

报告题目： Secure WiFi-based Indoor Positioning: Attacks and Countermeasures
报告时间：   2018年6月11日（星期一）下午 4：00-5：00
报告地点：   外围投注365B404
报告人：      张锐博士
报告人单位：特拉华大学计算机与信息科学系
报告人简介: Rui Zhang is an Assistant Professor in the Department of Computer and Information Sciences at the University of Delaware (UD). He received the Ph.D. degree in Electrical Engineering from Arizona State University in 2013, the M.E. degree in Communication and Information Systems from Huazhong University of Science and Technology in 2005, and the B.E. degree in Communication Engineering from Huazhong University of Science and Technology in 2001. Before joining the UD, he was an Assistant Professor in the Department of Electrical Engineering at the University of Hawaii from 2013 to 2016. His research interests are the security and privacy issues in wireless networks, mobile crowdsourcing, mobile systems for disabled people, cloud computing, and social networks. He is an Associate Editor of IEEE Internet of Things Journal. He was a general co-chair for Information Security Conference 2016 and has been a TPC member for various conferences such as IEEE INFOCOM, ACM MobiHoc, IEEE ICDE, IEEE SECON, and ACM ASIACCS. He received the NSF CAREER Award in 2017.

报告摘要:
Indoor positioning systems (IPSes) have great potential in facilitating human indoor activities and enabling many location-based services just like the GPS did for outdoor. IPS based on Received signal strength (RSS) fingerprints are the most classical IPS built upon the existing indoor WiFi infrastructure. While significant efforts have been made to improve the positioning accuracy of RSS fingerprint-based IPS, their security vulnerabilities have so far received little attention and remain underexplored. In this talk, I will first introduce how an attacker can severally degrade the positioning accuracy by either launching sophisticated signal strength attacks during the online positioning phase or polluting the RSS fingerprint database stored at the IPS server during the offline training phase. I will then present effective countermeasures to ensure robust positioning against these newly discovered attacks.

邀请人：刘树波张锡宁

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