学术讲座预告
时间：2016年6月17日（周五）上午9：30
地点：工业中心605室
主讲：Prof. Chunming Rong（容淳铭教授）
题目：Privacy and Accountability in Data Services
主讲人简介：
Prof. Chunming Rong is head of the Center for IP-based Service Innovation (CIPSI) at the University of Stavanger (UiS) in Norway, where his work focuses on data-intensive (big-data) analytics, cloud computing, security and privacy. He is an IEEE senior member and is honored as member of the Norwegian Academy of Technological Sciences (NTVA) since 2011. He is also an advisor for SINTEF ICT and has extensive contact network and projects in both the industry and academic. He was visiting chair professor at Tsinghua University (2011 – 2014) and served also as an adjunct professor at the University of Oslo (2005-2009). He is co-founder and chairman of the Cloud Computing Association (CloudCom.org) and its associated IEEE conference and workshop series. He is chair of IEEE Computer Society Special Technical Community (STC) for Cloud Computing since April 2014, and is representative of the IEEE Computer Society in steering board of the IEEE Cloud Computing Initiative. He is also the co-Editors-in-Chief of the Journal of Cloud Computing (ISSN: 2192-113X) by Springer and associate editor of the IEEE Transactions on Cloud Computing (TCC). He received award as Editor's Choice in Discrete Mathematics for 1999, ConocoPhillips Communication Award for 2007, and Sparebank-1 SR-bank Innovation Award for 2011. He coauthored a book titled "Security in Wireless Ad Hoc and Sensor Networks" published by John Wiley & Sons in 2009. Prof. Rong has extensive experience in managing large-scale R&D projects funded by both industry and funding agencies, such as the Norwegian Research Council and the European Framework and Horizon2020 Programs.
报告主要内容：
With Big-data processing and analytics, organizations and enterprises have increased the collection of data from individuals, and are increasingly developing business models involving analytics to gain deep insights into the data collected. It is essential to release and merge data to third-parties for more extensive analytics for which an organization may not have the necessary expertise. Data has to be anonymized prior to such release, to safeguard the privacy of individuals involved. While different algorithms with varying privacy guarantees have been proposed for anonymizing data, large scale distributed anonymization remains an under-explored topic. We proposes a framework and a distributed algorithm for anonymization of large data sets. The work focuses on datacenter environments, both private data centers and public clouds; and is compatible with modern data analytics frameworks like map-reduce and resilient distributed data sets (RDDs). We aims at minimizing identity, similarity and skins based attacks on anonymized data It also limits the difference (with respect to the original data set) in the distribution of sensitive attributes in data released, by adhering to the taxonomy tree of sensitive attributes in the original data set. Empirical evaluation of its scalability and efficiency is given. Cloud and IT service providers should be responsible for the data of their customers and users. However, accountability frameworks for distributed IT services is current still absent and makes it difficult for users to understand, influence and determine how their service providers honor their obligations. In the proposed EU A4Cloud project, we will create solutions to support users in deciding and tracking how their data is used by cloud service providers. By combining methods of risk analysis, policy enforcement, monitoring and compliance auditing with tailored IT mechanisms for security, assurance and redress.
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科研处
研究生处
电信学院
2016年6月15日
