Biography:
Sheng Zhong received his BS (1996), MS (1999) from Nanjing University, and his PhD (2004) from Yale University, all in computer science. He used to be on the faculty of SUNY Buffalo computer science and engineering, receiving NSF CAREER Award and early tenure promotion over there. Currently he is a professor at Nanjing University. He is a recipient of the National Science Fund for Distinguished Young Scholars of China, and has also been supported by the 1000-Talent Recruit Program of China (Youth Class). He is an Editorial Board Member of Science China Information Sciences, an Editor of IEEE Transactions on Vehicular Technology, and an Associate Editor of Information Sciences.
Title:
Privacy Preserving Computing and Min and k-th Min
Abstract: Protecting users' privacy is extremely important in mobile sensing applications. In this work, we study how an aggregator can quickly compute the minimum or the k-th minimum of users' data, without learning the data. Two protocols are built, based on random coding and an XOR-homomorphic encryption scheme. These protocols are proved to be secure in the semi-honest model. Empirical data demonstrates that our protocols have greatly improved the efficiency compared with previous protocols.