PhD, Professor, University of Louisville, Kentucky, USA
Building Secure Cloud Information System using Cloud Security Architecture Tool
Abstract: Todays commercial and government information systems include clouds, networks, data systems, and complex storage databases that contains sensitive personal information. These commercial and government organizations must be entrusted with security and privacy risk management to ensure their information systems operate securely and reliably. In order to provide structured guidance and framework NIST has developed extensive guidelines and specifications to assist organizations. The NIST 800 Series is a set of documents that describe United States federal government computer security policies to implement and manage the system information security risk. For example, SP 800-200 is Cloud Computing Security Reference Architecture specification to accelerate the securely adoption of cloud computing. SP 800-53 R4 defines the security and privacy controls recommended for each functional capability or micro-service a system implements. One of the issues with these standards is how an organization can implement these specifications. To provide this capability, a tool Cloud Security Architecture Tool (CSAT) is developed that aims to leverage the Cybersecurity Framework (CSF) to identify the NIST SP 800-53 security and privacy controls for cloud-based information systems by identifying the necessary functional capabilities the system needs to provide to support the organization's mission and the service the system is designed for. In this talk, we will discuss the motivation and significance of NIST’s specifications. In addition, it provides a discussion on the role of CSAT in an organization to enhance and facilitate adoption of secure cloud solution.
Anup Kumar (firstname.lastname@example.org) completed his Ph.D. from North Carolina State University and is currently a Professor of CECS Department at the University of Louisville. He is also the Director of Mobile Information Network and Distributed Systems (MINDS) Lab. His research interests include web services, wireless networks, distributed system modelling, and simulation. He has co-edited a book titled, “Handbook of Mobile Systems: Applications ands Services” published by CRC press in 2012. He is an Associate Editor of IEEE Transactions on Services Computing. He is also the Associate Editor of Internal Journal of Web Services Research and International Society of Computers and Their Application Journal. He is a member of IEEE Distinguished Visitor Program (2006-2008). He was the Chair of IEEE Computer Society Technical committee on Simulation (TCSIM) (2004-2007). He has published and presented over 150 papers. Some of his papers have appeared in ACM Multimedia Systems Journal, several IEEE Transactions, Wireless Communication and Mobile Computing, Journal of Parallel and Distributed Computing, IEEE Journal on Selected Areas in Communications etc. He was the Associate Editor of International Journal of Engineering Design and Automation 1995-1998. He has served on many conference program and organizing committees such as IEEE ISCC 2007, IEEE ICSW-2006, IEEE MASS-2005, IEEE SCC-2005, IEEE ICWS-2005, CIT-2005, IEEE MASCOTS, ADCOM 97 and 98. He has also edited special issues in IEEE Internet Magazine, and International Journal on Computers and Operations Research. He is a Senior Member of IEEE.
Prof. Chengnian Long
Shanghai JiaoTong University
Trusted Intelligent Internet of Things: Key Technologies and Application Cases
Abstract: This report introduces the use of blockchain technology to construct a trusted and distributed IoT system architecture to enhance IoT system security and data sharing, which can promote the application value for IoT in future digital economy. Key technologies include device autonomous identity and security authentication, distributed data storage and distribution, and distributed consensus protocol. We will introduce some application cases in intelligent transportation and smart medical care to explore the value of blockchain technology in the real economy.
First, many current critical infrastructures such as power grids, transportation systems, and medicine systems are emerging with the tight integration of physical processes and cyber world. Due to the crucial role of cyber-physical systems in everyday life, cyber-physical security needs to be promptly addressed. Particularly, his research group is focus on the security estimation and control of power grids and industrial control systems. Second, he has a long-term concern on the fundamental networking problem in Internet of Things, such as crowd sensing system, fog computing of intelligence gateway, MIMO wireless technology for smart devices. Particularly, his research group is focus on the sensing, computing, communication, and control integration of Internet of Vehicles (IoV). Third, the long-term view is to develop system intelligence for both CPS and IoT. An emerging trend is data-driven distributed intelligence system. Thus, the large-scale trust and reliable data is the power source for intelligence system. Furthermore, to apply the AI technology (deep learning and computer vision) from the laboratory to the real world that require a new approach to supporting the associated power, weight, space, and real-time constraints. Particularly, his research group is focus on investigating the blockchain technology to construct distributed intelligence system and developing the embedded computer vision and deep learning technology for UAV and autonomous vehicles.
Chengnian Long is a full professor of Department of Automation, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University. His research interest mainly focuses on the Cyber-Physical Systems (CPS), including: 1) Cyber-Physical Systems (CPS) Security: security estimation and control of CPS, intrusion detection system, blockchain security; 2) Internet of Things (IoT): crowd sensing, fog computing, internet of vehicle, wireless MIMO system and 3) Distributed Intelligence Systems: embedded computer vision for smart devices (UAV, Autonomous vehicles), blockchain.
Shanghai Tech University
AI-enabled Wireless Communication Networks
Dr. Yang Yang is currently a full professor with School of Information Science and Technology, ShanghaiTech University, China. Prior to that, he has held faculty positions at The Chinese University of Hong Kong, Brunel University (UK), University College London (UCL, UK), and SIMIT, Chinese Academy of Sciences (CAS, China).
Yang is a member of the Chief Technical Committee of the National Science and Technology Major Project "New Generation Mobile Wireless Broadband Communication Networks" (2008-2020), which is funded by the Ministry of Industry and Information Technology (MIIT) of China. In addition, he is on the Chief Technical Committee for the National 863 Hi-Tech R&D Program "5G System R&D Major Projects", which is funded by the Ministry of Science and Technology (MOST) of China. Yang is a General Co-Chair of IEEE DSP 2018 conference and a TPC Vice-Chair of IEEE ICC 2019 conference.
Yang's current research interests include wireless sensor networks, Internet of Things, Fog computing, Open 5G, and advanced wireless testbeds. He has published more than 200 papers and filed over 80 technical patents in wireless communications. He is a Fellow of the IEEE.
City University of Hong Kong
Optimal Network Decomposition for Next-Generation Mobile Communication Systems
Abstract: The fundamental idea of network decomposition is to break a large-scale network into smaller parts such that the subnetworks can operate in parallel, each with a much lower dimensionality. For large-scale wireless networks, the cellular structure is based on the idea of network decomposition, where the network is decomposed into multiple subnetworks, i.e., cells, according to the coverage of each base-station (BS). Such a decomposition scheme, nevertheless, leads to strong interference among subnetworks, which becomes increasingly significant as the density of BSs grows. For the next-generation cellular network where a massive amount of BSs need to be deployed to meet the ever-increasing demand of high data rate, it is of paramount importance to develop efficient network decomposition schemes to replace the current cellular structure. How to build such a decomposition framework, unfortunately, has remained largely unknown.
In this talk, I will introduce our recently proposed network decomposition theory for large-scale wireless networks. Specifically, starting from a novel bipartite graph representation of an infrastructure-based wireless network, I will show that in general the optimal network decomposition can be formulated as a graph partitioning problem. I will then demonstrate how to solve it by the proposed Binary Search based Spectral Relaxation (BSSR) algorithm. The performance of the proposed BSSR algorithm is further examined and compared to the current cellular structure and BS clustering in various scenarios. Significant gains are shown to be achieved by the proposed BSSR algorithm, which corroborates that the optimal network decomposition of next-generation cellular networks should be performed based on a bipartite graph where the geographical information of BSs and users are both included.
Dr. Lin Dai received the B.S. degree from Huazhong University of Science and Technology, Wuhan, China, and the M.S. and Ph.D. degrees from Tsinghua University, Beijing, China, all in electronic engineering. She is now a full professor of Department of Electronic Engineering of City University of Hong Kong.
She has broad interests in communications and networking theory, with special interests in wireless communications. Her recent research work focuses on modeling, performance analysis and optimal access design of next-generation mobile communication systems.
She was a co-recipient of the Best Paper Award at the IEEE Wireless Communications and Networking Conference (WCNC) 2007 and the IEEE Marconi Prize Paper Award (the annual Best Paper Award of IEEE Transactions on Wireless Communications) in 2009. She received The President's Award of City University of Hong Kong in 2017.
Prof. Guangxia Xu
Chongqing University of Posts and Telecommunications
Blockchain Data Sharing and Its Industry Case Study
Abstract: Due to the advanced features of openness, anonymity, immutability and decentralization of blockchain technology, it is currently a hot topic of interest to technology giants and business communities. Combining with big data, cloud computing and IoT, blockchain technology is a promising trend and is expected to ensure sharing data trustworthiness and security. Using the smart contract and distributed storage in blockchain to reduce costs, improve work efficiency and promote social development of the intelligent.
This talk will introduce disadvantages of traditional centralized data and definite advantages brought by blockchain in data sharing. Furthermore, we will propose the application of blockchain data sharing in different industries in detail, such as agriculture, IoT, medical health and so on. Especially, framework design, smart contracts and consensus mechanisms give our own methods. At last, we will talk about the point that blockchain promotes coordinated social development and shared economy.
Dr. Xu is currently Ph.D. adviser, vice director of Network and Information Security Engineering Center of Chongqing. She is a senior member of China Computer Federation (CCF); Blockchain Committee member; ACM and IEEE member; vice chairman of Information Security Association of Chongqing; expert of National Natural Science Foundation and committee member of Technical Committee on Fault Tolerant Computing of CCF. She has served as director of Big Data Security and Intelligence Analytics Technology Innovation Team in Chongqing. She was a visiting scholar at Stevens Institute of Technology, New Jersey, USA and a post-doctor at School of Communication and Information Engineering, Chongqing University.
Prof. Xu ‘s research interests include Blockchain Technology and Application, Big Data Security and Analytics, Network Security and Management, IoT Security and AI Security. Extensive and novel results have been accomplished and most of them have already been published through high-quality journal, conference papers and projects. She is in charge of one sub-project of National Science and Technology Support Projects, two projects of National Natural Science Foundation of China, one sub-project of information Security Projects of National Development and Reform Commission, and more. In addition, she is a reviewer for 《ACM Computing Surveys》、《IEEE Access》、《Digital Communications and Networks》、《International Journal of Geographical Information Science》, and member of the editorial board of 《Journal of Chongqing University of Posts and Telecommunications.
School of Computer Science and Engineering, Nanyang Technological University
Cyber-Physical Approach to Resilient City-Scale IoT Systems
Abstract: With the increasing connectivity and intelligence of massive objects, various city-scale systems such as utility infrastructures and transportation systems are evolving into their next generations for higher efficiency. However, they also face growing risks such as unexpected disturbances and even malicious attacks. Therefore, in the pursuit of the smart city vision, it is also important to enhance the resilience of these systems upon the contingency of these risks. In this talk, I will present our recent research on leveraging a city-scale physical process, i.e., the delivery of alternating current electricity, to achieve resilient timestamping and clock synchronization for Internet-of-Things objects found in electrified systems, smart ambient, and even on human bodies.
Dr. Rui Tan is an Assistant Professor at School of Computer Science and Engineering, Nanyang Technological University. Previously, he was a Senior Research Scientist at Advanced Digital Sciences Center, a Singapore-based research center of University of Illinois at Urbana-Champaign, and a postdoctoral Research Associate at Michigan State University. He received PhD degree from City University of Hong Kong. His research interests include sensor networks, Internet of things, and cyber-physical systems. He is the recipients of IPSN'17 and CPSR-SG'17 Best Paper Awards, IPSN'14 and PerCom'13 Best Paper Award Runner-Ups, and CityU Outstanding Academic Performance Award. He is a Senior Member of the IEEE.
Dr. Chih-Lin I
Chief Scientist, Wireless Technologies, China Mobile Research Institute
Bringing AI to the RAN
Chih-Lin I received her Ph.D. degree in electrical engineering from Stanford University. She has been working at multiple world-class companies and research institutes leading the R&D, including AT&T Bell Labs; Director of AT&T HQ, Director of ITRI Taiwan, and VPGD of ASTRI Hong Kong. She received the IEEE Trans. COM Stephen Rice Best Paper Award, is a winner of the CCCP National 1000 Talent Program, and has won the 2015 Industrial Innovation Award of IEEE Communication Society for Leadership and Innovation in Next-Generation Cellular Wireless Networks.
In 2011, she joined China Mobile as its Chief Scientist of wireless technologies, established the Green Communications Research Center, and launched the 5G Key Technologies R&D. She is spearheading major initiatives including 5G, C-RAN, high energy efficiency system architectures, technologies and devices; and green energy. She was an Area Editor of IEEE/ACM Trans. NET, an elected Board Member of IEEE ComSoc, Chair of the ComSoc Meetings and Conferences Board, and Founding Chair of the IEEE WCNC Steering Committee.
She was a Professor at NCTU, an Adjunct Professor at NTU, and currently an Adjunct Professor at BUPT. She is the Chair of FuTURE 5G SIG, an Executive Board Member of GreenTouch, a Network Operator Council Founding Member of ETSI NFV, a Steering Board Member of WWRF, a member of IEEE ComSoc SDB, SPC, and CSCN-SC, and a Scientific Advisory Board Member of Singapore NRF. Her current research interests center around “Green, Soft, and Open”.
Dr. Shui Yu
University of Technology Sydney, Australia
Big Data Privacy: A Machine Learning Perspective
Abstract: Big data is a revolution for our society. However, it also introduces a significant threat to data privacy. In this talk, we firstly review the current work in privacy protection under the framework of big data. Then we discuss the challenges in the domain from different angles, especially the machine learning aspects in field. We humbly hope this talk will shed light for forthcoming researchers to further explore the uncharted part of this promising land.
Shui Yu is currently a full Professor of School of Software, University of Technology Sydney, Australia. Dr Yu’s research interest includes Security and Privacy, Networking, Big Data, and Mathematical Modelling. He has published two monographs and edited two books, more than 200 technical papers, including top journals and top conferences, such as IEEE TPDS, TC, TIFS, TMC, TKDE, TETC, ToN, and INFOCOM. Dr. Yu initiated the research field of networking for big data in 2013. His h-index is 32.
Dr. Yu actively serves his research communities in various roles. He is currently serving the editorial boards of IEEE Communications Surveys and Tutorials, IEEE Communications Magazine, IEEE Internet of Things Journal, IEEE Communications Letters, IEEE Access, and IEEE Transactions on Computational Social Systems. He has served more than 70 international conferences as a member of organizing committee, such as publication chair for IEEE Globecom 2015, IEEE INFOCOM 2016 and 2017, TPC chair for IEEE BigDataService 2015, and general chair for ACSW 2017. He is a Senior Member of IEEE, a member of AAAS and ACM, the Vice Chair of Technical Committee on Big Data of IEEE Communication Society, and a Distinguished Lecturer of IEEE Communication Society.