NaNA2020 Keynote 1: |
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Speaker:
Prof. Xiangyang Li
Title:
Edge-Centric Intelligent Computing: Intelligence, Privacy and Applications
Affiliation:
University of Science and Technology of China, China
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| Abstract: Nowadays, we have witnessed the explosion of data and devices in the areas of IoT and mobile computing. Moreover, we are facing more and more complicated computation tasks, serious privacy and security problems, and critical delay requirements. All these challenges call for the application of edge computing to deploy computing resource closed to mobile users and the data source. In this talk, based on our own research results, we will mainly focus on the theory and platform implementation of edge intelligence, including online intelligence, distributed intelligence, as well as the privacy and security issues involved. We will also elaborate our current progress in the key applications of our edge platform such as Automatic Driving and AIoT Security.
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Short bio:
Dr. Xiangyang Li is currently a professor and Executive Dean at School of Computer Science and Technology, USTC and co-Chair of ACM China Council. He is an ACM Fellow (2019), IEEE fellow (2015), an ACM Distinguished Scientist (2014). He was a full professor at Computer Science Department of IIT, and an EMC Visiting Chair Professor at Tsinghua University (2013-2016). Dr. Li received MS (2000) and PhD (2001) degree at Department of Computer Science from University of Illinois at Urbana-Champaign. He received a Bachelor degree at Department of Computer Science from Tsinghua University, P.R. China, in 1995. His research interests include artificial intelligence of things, edge computing, privacy and security, data sharing and trading, and algorithms. His Google-scholar citation is more than 22,000, and H-index is 76. Dr. Li and his students won 7 best paper awards, won the best paper award, the best demo award and the best poster award from ACM MobiCom, and was selected as best paper candidates of ACM MobiCom twice. Dr. Li has served or is serving as an editor of several journals, including IEEE/ACM ToN, IEEE TPDS, and IEEE TMC.
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NaNA2020 Keynote 2: |
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Speaker:
Prof. Chao Shen
Title:
Data-Driven Security Analysis of Machine Learning Systems
Affiliation:
Xi’an Jiaotong University, China
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| Abstract:Human society is witnessing a wave of machine learning (ML) driven by deep learning techniques, bringing a technological revolution for human production and life. In some specific fields, ML has achieved or even surpassed human-level performance. However, most previous machine learning theories have not considered the open and even adversarial environments, and the security and privacy issues are gradually rising. Besides of insecure code implementations, biased models, adversarial examples, sensor spoofing can also lead to security risks, which are hard to be discovered by traditional security analysis tools. This talk reviews previous works on ML system security and privacy, revealing potential security and privacy risks. Firstly, we introduce a threat model of ML systems, including attack surfaces, attack capabilities and attack goals. Second, we analyze security risks and countermeasures in terms of four critical components in ML systems: data input (sensor), data preprocessing, machine learning model and output. Finally, we discuss future research trends on the security of ML systems. The aim is to arise the attention of the computer security society and the ML society on security and privacy of ML systems, and so that they can work together to unlock ML’s potential to build a bright future.
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Short bio:
Chao Shen is a Professor in School of Electronic and Information Engineering, and serves as the Associate Dean of School of Cyber Science and Engineering, at Xi’an Jiaotong University. He is also a member of Ministry of Education Key Lab for Intelligent Networks and Network Security. He was a research scholar in Computer Science Department of Carnegie Mellon University from 2011 to 2013. He has published over 70 papers in prestigious journals and conferences of cyber security and artificial intelligence fields such as USENIX Security, ACM CCS, IEEE TDSC, IEEE TIFS, Automatica, IEEE TNNLS, and ACM TKDD. He was the recipient of NSFC Excellent Young Scientists Fund. He serves as an associate editor of several international journals, as well as organization committee member or program committee member of several academic conferences.
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2018-2020
All Rights Rreserved.
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