学术报告

当前位置: 首页 > 学术报告 > 正文

智能计算研究所前沿报告

发布时间:2018-10-16 编辑:周兆芸 来源:


Title: Communication-Efficient and Privacy-Preserving Data Aggregation without Trusted Authority

Speaker: 华强胜,华中科技大学副教授,博士生导师

Time: 2018年10月18日上午9:30 - 10:30

Place:金沙集团3354cm332会议室

Abstract:

    Privacy-preserving data aggregation has been extensively studied in the past decades. However, most of these works target at specific aggregation functions such as additive or multiplicative aggregation functions. Meanwhile, they assume there exists a trusted authority which facilitates the keys and other information distribution. In this paper, we aim to devise a communication efficient and privacy-preserving protocol that can exactly compute arbitrary data aggregation functions without trusted authority. In our model, there exist one untrusted aggregator and participants. We assume that all communication channels are insecure and are subject to eavesdropping attacks. Our protocol is designed under the semi-honest model, and it can also tolerate to collusive adversaries. Our protocol achieves -source anonymity. That is, for the source of each collected data aparting from the colluded participants, what the aggregator learns is only from one of the noncolluded ones. Compared with recent work [1] that computes arbitrary aggregation functions by collecting all the participants’ data using the trusted authority, our protocol increases merely by at most a factor of in terms of computation time and communication cost. The key of our protocol is that we have designed algorithms that can efficiently assign unique sequence numbers to each participant without the trusted authority. Then, we consider a practical scenario where participants may join or leave in the system model. We propose efficient protocols for both dynamic join and leave. Our protocols utilize a basic oblivious transfer scheme and the existing unique sequence numbers of the existing participants to reduce the communication cost.

报告人简介:

    华强胜,华中科技大学副教授,博士生导师,2009年博士毕业于香港大学。主要研究方向为网络与分布式计算理论、算法及应用,在等重要国际会议和期刊发表论文60余篇。承担多项国家自然科学基金以及国家重点研发计划子课题项目。担任网络和分布式计算国际系列主流会议程序委员会委员和国际期刊编委。


联系我们

地址: 山东省青岛市即墨区滨海公路72号

           金沙集团3354cm(青岛)第周苑C座

邮编:266237

院办电话:(86)-532-58630622

本科招生电话:(86)-532-58630176

研究生招生电话:(86)-532-58630610

学院微信公众号

山大微信公众号