Spring 2011
Anna Squicciarini
February 25, 2011
Speaker: Anna Squicciarini
Assistant Professor
College of Information Sciences, Penn State University
Title
Privacy Enhancing Techniques for Social Network
Time/Location
2:30pm
Information Sciences Building, Room 404
Abstract:
In this seminar, I will present my recent work in Access Control and Privacy issues for Social Network sites.
I will discuss security implications related to disclosure of inappropriate data across Social Networks, and use as a case study the problem of digital images distribution and misuse. Two specific issues will be discussed: first, how to assess co-ownership, if multiple users appear to be stakeholders of the same image. Second, we will look into the problem of image control within and across social network sites. I will discuss our approach to these issues, which draw from game theory and algorithmic results. I will provide an overview of the deployed prototype and provide some interesting insights obtained from performance and user studies. Our studies provided us with interesting findings, in terms of users’ perception of privacy and protection from security threats. I will conclude with highlighting interesting issues that represent open problems and outlining new lines of research for this work.
Biography:
Dr. Anna Squicciarini joined Penn State’s College of Information Sciences and Technology as an assistant professor in January 2008.
Squicciarini’s main research interests include trust negotiations, privacy, digital identity management, and access control for grid computing systems. She has been the main architect of Trust-X, an advanced trust negotiation system supporting privacy policies, anonymity, and recovery techniques. Currently, she is investigating as part of an NSF funded project, security issues in the context of social networks and is developing trust negotiation protocols in peer-to-peer platforms.
Squicciarini earned her Ph.D. in Computer Science from the University of Milan, Italy, in March 2006. In July 2002, she received the equivalent of a combined bachelor’s/master’s degree in Computer Science, also from the University of Milan.
From 2006 until the end of 2008, Squicciarini was a post-doctoral research associate at Purdue University, where she expanded her research interests to include security for grid systems and identity theft. She was involved in numerous NSF research projects on digital identity management and security for grid systems.
Earlier, in 2003, Squicciarini was a visiting researcher at the Swedish Institute of Computer Science in Stockholm, and the following year she was a research scholar at Colorado State University in Fort Collins, CO.
Squicciarini is the author or co-author of more than 35 conference papers and journal articles. Currently, she is co-authoring a book on Web services security.
She serves as a program committee member for many relevant security and privacy conferences, such as ACM Sacmat 2011, WWW 2011, and IEEE Collaborative-Com 2008.
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Guanhua Yan
March 25
Speaker: Dr. Guanhua Yan
Technical Staff Member
Information Sciences Group, Los Alamos National Laboratory
Title
Combating Cyber Threats with High-Performance Computers
Time/Location
12:00pm
Information Sciences Building, Room 404
Abstract:
The openness of the Internet is a double-edged sword: although it brings tremendous resources available on the Internet to the general public, it also can be exploited by malicious parties to mount large-scale cyber attacks, such as DDoS, malware, and botnets. To combat these cyber threats, researchers from both the academia and the industry have made great efforts in hardening the security of existing computer and network systems.
In this talk, I would like to discuss how to leverage the rich computational resources available at a national lab to help reduce cyber threats. Our efforts in this regard can be classified into three categories. First, we apply large-scale modeling and simulation techniques to understand emerging cyber threats, such as peer-to-peer botnets, and malware propagation in online social networks. Second, we use high-performance computers to mine intensive network traffic and large online social networks for anomalous activities. Third, we develop large-scale high-fidelity models to assess the risks of critical infrastructure such as the Internet backbone and SCADA networks.
Biography:
Guanhua Yan obtained his Ph.D. degree in Computer Science from Dartmouth College, USA, in 2005. From 2003 to 2005, he was a visiting graduate student at the Coordinated Science Laboratory of the University of Illinois at Urbana-Champaign. He is now working as a Technical Staff Member in the Information Sciences Group (CCS-3) at Los Alamos National Laboratory. His current research interests are cyber modeling and simulation, anomaly detection, infrastructure protection, and data privacy. During his graduate studies, he worked on large-scale network modeling and simulation, and his Ph.D. work on coarse-level traffic simulation models won the best paper award at the 19th Workshop on Parallel and Distributed Simulation (PADS 2005).