题目：Energy Big Data Analytics and Security: Challenges and Opportunities 

　　报告人：Prof. Jiankun Hu , UNSW Canberra, Australia. 

　　时间： 2016年6月3日（星期五）， 上午09:30  

　　地点：中国科学院信息工程研究所3号楼（B2座）3224室 

　　Abstract: 

　　The limited available fossil fuels and the call for sustainable environment have brought about new technologies for the high efficiency in the use of fossil fuels and introduction of renewable energy. Smart grid is an emerging technology that can fulfill such demands by incorporating advanced information and communications technology (ICT). The pervasive deployment of the advanced ICT, especially the smart metering, will generate big energy data in terms of volume, velocity, and variety. The generated big data can bring huge benefits to the better energy planning, efficient energy generation and distribution. As such data involve end users’ privacy and secure operation of the critical infrastructure, there will be new security issues. This paper is to survey and discuss new findings and developments in the existing big energy data analytics and security. Several taxonomies have been proposed to express the intriguing relationships of various variables in the field. 

　　Bio: 

　　Dr. Jiankun Hu is Professor at the School of Engineering and IT, University of New South Wales (UNSW) Canberra (also named UNSW at the Australian Defence Force Academy (UNSW@ADFA), Canberra, Australia. He is the invited expert of Australia Attorney-General’s Office assisting the draft of Australia National Identity Management Policy. Prof. He has served at the Panel of Mathematics, Information and Computing Sciences (MIC), ARC ERA (The Excellence in Research for Australia) Evaluation Committee 2014. Prof. Hu’s research interest is in the field of cyber security covering intrusion detection, sensor key management, and biometrics authentication. He has many publications in top venues including IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Computers, IEEE Transactions on Parallel and Distributed Systems (TPDS), IEEE Transactions on Information Forensics & Security (TIFS), Pattern Recognition, and IEEE Transactions on Industrial Informatics.