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Keynote by Mike Reiter (University of North Carolina at Chapel Hill, USA)"Side Channels in Multi-tenant Environments"With the growth of cloud computing, the security provided by public clouds to their tenants is increasingly being scrutinized, in part because these clouds arrange for mutually distrustful tenants to simultaneously execute tasks on the same hardware. In this talk we explore a long-suspected but, to date, largely hypothetical attack vector in public clouds, namely "side-channel attacks" in which one tenant might learn sensitive information about another tenant simply by running on the same hardware with it, but without violating the logical access control enforced by the cloud's isolation software (hypervisor or operating system). Specifically, we demonstrate the practicality of damaging cross-tenant side-channel attacks on modern hypervisors and operating systems, including some that we have demonstrated on commercial public clouds. We will then describe various approaches we have developed to defend against side-channel attacks in cloud environments, both inexpensive defenses against our specific attacks and more holistic but expensive protections.Biography:Michael Reiter is the Lawrence M. Slifkin Distinguished Professor in the Department of Computer Science at the University of North Carolina at Chapel Hill (UNC). He received the B.S. degree in mathematical sciences from UNC in 1989, and the M.S. and Ph.D. degrees in Computer Science from Cornell University in 1991 and 1993, respectively. He joined AT&T Bell Labs in 1993 and became a founding member of AT&T Labs – Research when NCR and Lucent Technologies (including Bell Labs) were split away from AT&T in 1996. He then returned to Bell Labs in 1998 as Director of Secure Systems Research. In 2001, he joined Carnegie Mellon University as a Professor of Electrical & Computer Engineering and Computer Science, where he was also the founding Technical Director of CyLab. He joined the faculty at UNC in 2007.Dr. Reiter's research interests include all areas of computer and communications security and distributed computing. He regularly publishes and serves on conference organizing committees in these fields. He served as program chair for the the flagship computer security conferences of the IEEE, the ACM, and the Internet Society, and of the flagship dependability conference of the IEEE; as Editor-in-Chief of ACM Transactions on Information and System Security; and on the editorial boards of IEEE Transactions on Software Engineering, IEEE Transactions on Dependable and Secure Computing, the International Journal of Information Security, and Communications of the ACM. He also served on the Emerging Technology and Research Advisory Committee for the United States Department of Commerce for four years. Dr. Reiter was named an ACM Fellow in 2008 and an IEEE Fellow in 2014.
Keynote by John C.S. Lui (Chinese University of Hong Kong, Hong Kong)"Sampling Large Networks: Algorithms and Applications"Often times, large networks can be represented as graphs. For example, the Internet topology can be represented as an undirected graph while large logical networks (e.g., Facebook, Twitter,..etc) can be represented as either directed or undirected graphs. For these graphs, characterizing node pair relationships is important for applications such as friend recommendation and interest targeting in online social networks (OSNs). Due to the large scale nature of such networks, it is infeasible to enumerate all user pairs and so sampling is used. In this talk, we show that it is a great challenge even for OSN service providers to characterize user pair relationships when they possess the complete graph topology. The reason is that when sampling techniques (i.e., uniform vertex sampling and random walk) are naively applied, they can introduce large biases, in particular, for estimating similarity distribution of user pairs with constraints such as existence of mutual neighbors. Estimating statistics of user pairs is even more challenging in the absence of the complete topology information, since an unbiased sampling technique such as uniform vertex sampling is usually not allowed, and exploring the OSN graph topology is expensive. To address these challenges, we present asymptotically unbiased sampling methods to characterize user pair properties. We also show potential applications and discuss future research work.Biography:John C.S. Lui is currently the Choh-Ming Li Professor of the Computer Science & Engineering Department at The Chinese University of Hong Kong. His current research interests are in network sciences, network economics, network/system security (e.g., cloud security, mobile security, ...etc), large scale distributed systems and performance evaluation theory. John received various departmental teaching awards and the CUHK Vice-Chancellor's Exemplary Teaching Award, as well as the CUHK Faculty of Engineering Research Excellence Award (2011-2012). He is a co-recipient of the IFIP WG 7.3 Performance 2005, IEEE/IFIP NOMS 2006 and SIMPLEX'14 Best Paper Awards. He is an elected member of the IFIP WG 7.3, Fellow of ACM, Fellow of IEEE, Senior Research Fellow of the Croucher Foundation and is currently the chair of the ACM SIGMETRICS. His personal interests include films and general reading.
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