Program (June 20 2023 at 3pm - 6.30pm local time)

Keynote Talk 1: Sara Foresti (Universita' degli Studi di Milano)
Session Chair: Dr. Suryadipta Majumdar (Concordia University, Canada)
3pm - 4pm: "Controlled distributed computations in the cloud"
Abstract: Data, which are at the basis of decision making processes, are one of the most valuable resources in our society. Companies and organizations generate and collect huge amounts of information, and are willing to collaborate and share their data for knowledge extraction (e.g., for medical research). In such a scenario, the current ICT environment offers a variety of opportunities for leveraging economically convenient and flexible storage and computational services. Data may however be sensitive or company-confidential. Therefore, data need to be properly protected against non authorized accesses. Also, both direct and indirect information flows implied by distributed collaborative computations need to be regulated. This talk will focus on recent approaches for enabling collaborative computations combining data sources under the control of different authorities, while regulating data exchanges among collaborating parties.
Bio: Sara Foresti is a professor at the Università degli Studi di Milano, Italy. Her research interests are in the area of data security and privacy, with particular consideration of data protection in emerging scenarios. Within this area, she has published more than 100 papers in journals, conference proceedings, and books. She has been a visiting researcher at George Mason University, VA, USA. She chairs the IFIP WG 11.3 on Data and Applications Security and Privacy. She is IEEE senior member (2016). She received the IFIP WG 11.3 Outstanding Research Contributions Award (2019). https://foresti.di.unimi.it/
Paper Presentations
Session Chair: Dr. Kallol Kirshna Karmakar (University of Newcastle, Australia)
4.15pm - 4.45pm: "slytHErin: An Agile Framework for Encrypted Deep Neural Network Inference", Francesco Intoci, Sinem Sav, Apostolos Pyrgelis, Jean-Philippe Bossuat, Juan-Ramon Troncoso-Pastoriza and Jean-Pierre Hubaux
4.45pm - 5.15pm: "Trust Management Framework for Containerized Workloads – Applications to 5G Networks", Aicha Miloudi, Luis Suarez, Nora Cuppens-Boulahia, Frédéric Cuppens and Stere Preda
Keynote Talk 2: Rongxing Lu (University of New Brunswick)
Session Chair: Dr. Alessandro Brighente (University of Padova, Italy)
5.30pm - 6.30pm: "Toward Privacy-Preserving Aggregate Reverse Skyline Query with Strong Security"
Abstract: It has been witnessed that Aggregate Reverse Skyline (ARS) query has recently received a wide range of practical applications due to its marvelous property of identifying the influence of query requests. Nevertheless, the query users may hesitate to participate in such query services as the query requests and query results may leak sensitive personal data or valuable business data assets to the service providers. To tackle the concerns, a promising solution is to encrypt the query requests, conduct the ARS queries over encrypted query requests without decrypting, and return the encrypted query results. Unfortunately, many existing solutions are either deployed over a two-server model or unable to fully preserve query privacy. In this talk, we present a novel privacy-preserving aggregate reverse skyline query (PPARS) scheme on a single server model while ensuring full query privacy. Specifically, we first transform the problem of ARS query into a combination of set membership test and logical expressions. Then, by employing the prefix encoding technique, bloom filter technique, and fully homomorphic encryption, we run the transformed logical expressions to obtain the encrypted aggregate values without leaking query requests, query results, and access patterns. Furthermore, we propose an interpolation-based packing technique to improve the communication efficiency of PPARS. Detailed and formal security analysis demonstrates that our proposed schemes can guarantee strong security. In addition, extensive experiments are conducted, and the results validate the efficiency of our proposed schemes.
Bio: Rongxing Lu is a Mastercard IoT Research Chair, a University Research Scholar, an associate professor at the Faculty of Computer Science (FCS), University of New Brunswick (UNB), Canada. Before that, he worked as an assistant professor at the School of Electrical and Electronic Engineering, Nanyang Technological University (NTU), Singapore from April 2013 to August 2016. Rongxing Lu worked as a Postdoctoral Fellow at the University of Waterloo from May 2012 to April 2013. He was awarded the most prestigious “Governor General’s Gold Medal”, when he received his PhD degree from the Department of Electrical & Computer Engineering, University of Waterloo, Canada, in 2012; and won the 8th IEEE Communications Society (ComSoc) Asia Pacific (AP) Outstanding Young Researcher Award, in 2013. Dr. Lu is an IEEE Fellow. His research interests include applied cryptography, privacy enhancing technologies, and IoT-Big Data security and privacy. He has published extensively in his areas of expertise. Currently, Dr. Lu serves as the Chair of IEEE ComSoc CIS-TC (Communications and Information Security Technical Committee), and the founding Co-chair of IEEE TEMS Blockchain and Distributed Ledgers Technologies Technical Committee (BDLT-TC). Dr. Lu is the Winner of 2016-17 Excellence in Teaching Award, FCS, UNB.