題目：Balancing Data Privacy and Utility

　　報告人：Hua Wang

　　時間：2024年11月22日(周五)，10：30-11：30

　　會議地點：31-904

　　報告摘要：

　　Distributed database system (DDBS) technology has shown its advantages with respect to query processing efficiency, scalability, and reliability. Moreover, by partitioning attributes of sensitive associations into different fragments, DDBSs can be used to protect data privacy. However, it is complex to design a DDBS when one has to optimize privacy and utility in a time-varying environment. This talk will introduce a distributed prediction-randomness framework for the evolutionary dynamic multiobjective partitioning optimization of databases. In the proposed framework, two sub-populations contain individuals representing database partitioning solutions. One sub-population utilizes a Markov chain-based predictor to predict discrete-domain solutions for database partitioning when the environment changes, and the other sub-population utilizes the random initialization operator to maintain population diversity. In addition, a knee-driven migration operator is utilized to exchange information between two sub-populations. Experimental results show that the proposed algorithm outperforms the competing solutions with respect to accuracy, convergence speed, and scalability.

　　報告人簡介：

　　Hua Wang is now a full time professor in the Institute for Sustainable Industries and Liveable Cities (ISILC) at Victoria University.? Hua carries out research on machine learning and data analysis, with a particular focus on data mining, artificial intelligence, deep learning, big data, privacy preserving, access control and cyber security. As a Chief Investigator, Hua has successfully received 11 large Australian Research Council (ARC) grants including seven discovery grants and three linkage grants with AU$10.0M since 2006. Hua has published 400 refereed scholar papers with 14000+ citations, including 81 Q1 (ERA2018 ranked) Journal papers in machine learning, cyber security, Artificial Intelligence, privacy preserving and data analysis. Hua's h-index is 69 based on Google Scholar website. As a principal supervisor, he currently has 14 PhD students at VU.Hua is Editor-in-Chief, Featured Journals, European Alliance for Innovation (EAI) Transactions on Scalable Information Systems, and also editor for PLOS ONE and World Wide Web Journal, Springer. He is involved in many prestigious international conferences such as PC members (ICDE2022-24, AAAI2019, IJCAR2022, 23) and chairs for the International Conference on Web Information Systems Engineering (WISE) 2015-2018.