Keynote (Main Conference)

last update: 7 May, 2022

New Multiparty Computational Model:
From Nakamoto to YOSO

Prof. Tal Rabin
Prof. Tal Rabin
University of Pennsylvania
United States of America
Abstract: Nakamoto introduced a mechanism for leader election via proof of work, and allowed this dealer to speak once. In this setting parties do not have inputs and they output a value which they calculated. Jing and Micali took this idea a step further and showed that Byzantine agreement, a function where parties have inputs but no private information, can be reached in a setting where each party speaks only once. This was achieved by introducing the notion of player replaceability. In our recent works we have shown that any function, including those where parties have secret inputs, can be computed in the YOSO (you only speak once) model.
Speaker’s Bio: Tal Rabin is the Rachleff Family Professor of Computer Science at University of Pennsylvania and a consultant to Algorand Foundation. Prior to joining UPenn she has been the head of research and Algorand Foundation, prior to that she was at IBM Research for 23 years as a Distinguished Research Staff Member and the manager of the Cryptographic Research Group. She received her PhD from the Hebrew University in 1995.
Tal’s research focuses on secure multiparty computation, threshold cryptography, and proactive security and recently adapting these technologies to the blockchain environment. Her works have been instrumental in forming these areas.
Tal is an ACM Fellow, an IACR (International Association of Cryptologic Research) Fellow and member of the American Academy of Arts and Sciences. Tal’s work won the 30 year test of time award at STOC. She is the 2019 recipient of the RSA Award for Excellence in the Field of Mathematics. She was named by Forbes in 2018 as one of the Top 50 Women in Tech in the world. In 2014 Tal won the Anita Borg Women of Vision Award winner for Innovation and was ranked by Business Insider as the #4 on the 22 Most Powerful Women Engineers.
She has served as the Program and General Chair of the leading cryptography conferences and as an editor of the Journal of Cryptology. She has initiated and organizes the Women in Theory Workshop, a biennial event for graduate students in Theory of Computer Science. Tal is currently the chair of the SIGACT Executive Board and she has served as a member of the SIGACT Executive Board and a council member of the Computing Community Consortium.

Cellular Security:
Why is it difficult?

Prof. Yongdae Kim
Prof. Yongdae Kim
Korea Advanced Institute of Science and Technology
Korea
Abstract: In the last 10 years, I have been working on various cellular security problems publishing more than 10 papers. The topics include privacy, accounting, service security, Middleboxes and IPV6, automatic performance analysis, (semi-)automatic security analysis, and physical layers. Throughout these studies, and interactions with device vendors, carriers and 3GPP/GSMA representatives, I found several fundamental problems cellular industry is facing. I believe these problems could be the root cause for many of the vulnerabilities found by researchers.
I will first explain 5 key insights that distinguish the cellular network security from traditional network security, including generation changes (4G vs. 5G), governance and closedness issues. I then talk about several technical difficulties cellular security research is facing. Several real examples will be given to connect concrete vulnerabilities and those technical difficulties. At the end of the talk, I will briefly talk about some suggestions to improve security of cellular networks.
Speaker’s Bio: Yongdae Kim is a Professor in the Department of Electrical Engineering, and the Graduate School of Information Security at KAIST. He received PhD degree from the computer science department at the University of Southern California under the guidance of Gene Tsudik in 2002. Before joining KAIST in 2012, he was a professor in the Department of Computer Science and Engineering at the University of Minnesota - Twin Cities for 10 years. He served as a KAIST Chair Professor between 2013 and 2016, and a director of Cyber Security Research Center between 2018 and 2020. He is a program committee chair for ACM WISEC 2022, was a general chair for ACM CCS 2021, and served as an associate editor for ACM TOPS, and a steering committee member of NDSS. His main research interests include novel attacks for emerging technologies, such as drone/self-driving cars, cellular networks and Blockchain.

Differentially Private Data Synthesis:
State of the Art and Challenges

Prof. Ninghui Li
Prof. Ninghui Li
Purdue University
United States of America
Abstract: Differential privacy has been accepted as the de facto notion for protecting privacy. Companies and government agencies use differential privacy for privacy-preserving data analysis. For example, the US census bureau applied differential privacy in the 2020 census. One important approach to use a private dataset is to generate a synthetic dataset that is similar to the private dataset in a way that satisfies differential privacy. This enables data analysts to directly apply existing algorithms for performing data analysis. Furthermore, as additional data analysis tasks performed on the published dataset are post-processing, they do not incur additional privacy cost. In recent years, US National Institutes of Standards and Technology ran two competitions on differentially private data synthesis, which drove the development of practically effective data synthesis algorithms.
In this talk, I will discuss the current state of the art for private data synthesis, with a focus on those approaches that have performed well in the NIST competitions. One family of approaches uses probabilistic graphical models. My group's approach uses private marginals and a procedure that is similar to Iterative Proportional Fitting, which has been studied in many fields. We also discuss the remaining challenge and open questions.
Speaker’s Bio: Ninghui Li is Samuel D. Conte Professor of Computer Science at Purdue University. He received a Bachelor's degree from the University of Science and Technology of China (USTC)'s Special Class of Gift Young in 1993, and a Ph.D. in Computer Science from New York University in 2000. His research interests are in security and privacy, on which he has published over 180 referred papers. He has received multiple best paper awards and test of time paper awards in security and database conferences. He is serving as Editorin-Chief for ACM Transactions on Privacy and Security since 2020, and has served in many leadership roles in the research community, including Chair of ACM Special Interest Group on Security, Audit and Control (SIGSAC) from 2017 to 2021. He is a fellow of ACM and of IEEE.