报告题目：Secure Computation & Data Sketching: A Happy Marriage
主 讲 人：Changyu Dong，Newcastle University, UK
报告时间：2019年7月17日 上午10:00
报告地点：重庆大学A区主教学大楼1811
报告摘要: Secure computation has been proven to be an essential tool for building privacy preserving systems. However, its practicality is often under debate. Despite significant improvements recently, secure computation is still orders of magnitude slower than computation in the clear. Even with the latest advancement, realising many "killer apps", which are often data intensive, is still a mission impossible in secure computation. On the other hand, in response to the Big Data challenge, the data sketching approach has quickly gained popularity in data sciences. Roughly, one can compress a large amount of data into a small data structure (a.k.a. sketch) whose size is significantly sub-linear to the original data size, and later approximate certain characteristics of the original data. In this talk, I will present our experience in combining secure computation and data sketching, demonstrate the benefit in terms of scalability, and report on a delightful surprise coming out of the combination.
主讲人介绍：Changyu Dong is a senior lecturer in security at Newcastle University, UK. He obtained his PhD from the Department of Computing at Imperial College London in 2009. His research interests fall under the broad heading of cyber security, including applied cryptography, cloud security, data privacy and blockchain. He has published more than 30 research papers in major journals and international conferences, including the most prestigious venues in security such as ACM CCS, ESORICS and Journal of Computer Security (JCS), IEEE Transactions on Dependable and Secure Computing (TDSC) and IEEE Transactions on Information Forensics and Security (TIFS). Three of his papers were selected as best paper at international conferences. He has served on and chaired program committees for many conferences and workshops, and is a regular invited reviewer for top international journals. Currently, he leads an EPSRC project “Practical Data-intensive Secure Computation: a Data Structural Approach”.
