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题目：Securing the neighborhood in smart grid systems

报告人：Fengjun Li

时间：2012.06.14（星期四）上午9:30-10:30

地点：4303（会议室）

报告内容摘要：

Envisioned as the next-generation approach for large-scale electricity delivery and management system, the smart grid has introduced computation and communication capabilities into traditional power grids to make them "smart" and "connected". Through the Advanced Metering Infrastructure (AMI), smart meters communicate with electrical appliances at households and the control centers at the utility companies to achieve smart power generation, distribution, pricing, and other advanced management functions. With all the advantages introduced by smart grids, security and privacy naturally become one of the critical concerns that people may have about the smart system.

In this talk, I will introduce two projects on security and privacy protection on the household and neighborhood side of the smart grid system. First, I will present a data aggregation approach to securely and efficiently collect aggregated information from distributed smart meters in the wireless mesh based neighborhood area network (NAN). Homomorphic cryptosystems are employed to enable privacy-preserving in-network operations, which provide better efficiency and scalability without sacrificing security. Next, I will introduce S2A, a security protection solution for smart devices. S2A employs machine learning technologies to provide smart and flexible protection for smart household appliances. It integrates device security, usability and pricing factors to generate an optimal operational strategy, which ensures appliances security while providing good usability and economic efficiency.

报告人简介：

Fengjun Li is an assistant professor of the Department of Electric Engineering and Computer Science at the University of Kansas. She holds a Ph.D. degree in Information Sciences and Technology from the Pennsylvania State University in 2010, an M.Phil from the Chinese University of Hong Kong in 2004, and a B.S. from the University of Science and Technology of China in 2001. She is currently a member of the Information Assurance Lab at the Information and Telecommunication Technology Center and her research interests span a wide range of security and privacy topics in distributed information systems, database systems, and communication networks. More recently, she is working on online social networks and smart grid systems.

题目：Stalking Online: on User Privacy in Social Networks

报告人：Bo Luo

时间：2012.06.14（星期四）上午10:30-11:30

地点：4303（会议室）

报告内容摘要：

With the extreme popularity of Web and online social networks, a large amount of personal information has been made available over the Internet. On the other hand, advances in information retrieval, data mining and knowledge discovery technologies have enabled users to efficiently satisfy their information needs over the Internet or from large-scale data sets. However, such technologies also help the adversaries such as web stalkers to discover private information about their victims from mass data.

In this talk, I will briefly cover two research projects on user privacy in social networks at the InfoSec group of the University of Kansas. The goal is to answer two questions: “how identifiable we are?” and “who is more likely to (accidentally) disclose our information?”

We first study privacy-sensitive information that is accessible from the Web, and how these information could be utilized to discover personal identities. In the proposed scenario, an adversary is assumed to possess a small piece of “seed” information about a targeted user, and conduct extensive and intelligent search to identify the target. I will introduce two types of attackers, namely tireless attackers and resourceful attackers, and then analyze detailed attacking mechanisms that could be performed by these attackers, and quantify the threats of both types of attacks to general Web users. Next, I will discuss how information flows among users in social networks, and how we can utilize such knowledge to help protect private information. In particular, we introduce a content-based user behavior model, which predicts how users would react to their friends’ posts.

报告人简介：

Bo Luo got his Ph.D. in information sciences and technology from the Pennsylvania State University in 2008, and joined the faculty of department of Electrical Engineering and Computer Science at the University of Kansas. Prior to that, he got an M.Phil degree from the Chinese University of Hong Kong and a B.E. degree from University of Science and Technology of China (USTC). He was an intern at IBM Silicon Valley Lab during the summer of 2006 and 2007. He is currently a member of the Information Assurance Lab at ITTC, with research interests on information security and privacy in distributed information systems, social networks and Web, smart grids, etc. His homepage could be found at: http://www.ittc.ku.edu/~bluo/