Prof. Shuang-Hua Yang, FIET, FInstMC, SMIEEE, is currently serving as the Vice Dean for Academic Affairs of Graduate School and a chair professor in the Department of Computer Science and engineering at SUSTech (Southern University of Science and Technology). Before joined SUSTech Professor Yang spent over 23 years in the UK Higher Education. He was the Head of Department of Computer Science at Loughborough University from 2014 to 2016. He joined Loughborough University in 1997 as a research assistant, and progressing to a research fellow in 1999, a lecturer in 2000, a senior lecturer in 2003, a professor in 2006, and Head of Department of Computer Science in 2014. He was awarded a Doctor of Science degree, a higher doctorate degree, in 2014 from Loughborough University to recognize his scientific achievement in his academic career. He is also an appointed expert at the national level in China. His research interests are mainly focused on Internet of Things and Cyber-Physical Systems. He authored four research monographs and over 200 academic papers.
Title: Protocol Reverse Engineering for Industrial Control Protocols
Abstract: This talk addresses the challenges in
building the connectivity between IoT (Internet of
Things) devices due to the proprietary characteristics
of various existing communication protocols.
Protocol reverse engineering (PRE) is an automatic or semi-automatic technique for reverse-parsing protocol field formats, semantics, and protocol state machines, based on network protocol data or executable programs, with or without mastering prior knowledge. Network PRE assists in building the connectivity between IoT devices. The data transmission among IoT devices rely on Industrial Control Protocol (ICP).
The ICPs are distinguishing from the standard network
protocols due to its strong real-time, generally
private, binary, and non-encrypted characteristics. The
existing PRE method presents certain limitations in
analyzing industrial control protocols. Therefore, a
mathematical model is required in protocol parsing, and
artificial intelligence (AI) is adopted to realize the
semi-automatic and automatic parsing of industrial
This talk first systematically introduces the development process and significance of protocol reverse engineering and then focuses on applying industrial control protocol parsing in the industrial Internet. Finally, a simple scheme of ICP is utilized for demonstrating the methods of protocol field division, protocol semantic recognition, and protocol state machine deduction.
Prof. Dr Lili Yang is working in Southern University of Science and Technology in Shenzhen, China. She is also a reader in the School of Business and Economics at Loughborough University, UK. She has conducted a significant amount of research both independently and working in team. As the principal investigator she has led 14 projects and carried out 6 projects as co-investigator. The total budget has reached to over £5 million. Her recent publications appear in the top journals such as Applied Energy, Information Systems Research, European Journal of Operational Research, Technological Forecasting and Social Changes, to be named. She was invited by the UK Cabinet Office and gave a presentation to their staff in London. Her research has generated impact to the research community in the whole world.
Title: Big Data Based Urban Public Safety Risks Prevention and Control
Abstract: This talk will introduce an ongoing national key research project on public safety risk prevention and control funded by the Ministry of Science and Technology of China (MOST). The work uses Shenzhen, a smart city, as a case study and aims to create an open, shared, integrated, reproducible, and related public safety data management model with the new concept of “separation of data and use, and intelligence driven”. The ultimate objective of the project is to form a public safety big data management standard system. The talk will describe the main research content of the project including: platform architecture design, gathering public safety big data, multi-source data fusion and secure sharing technologies, and establishing openness , sharing, fusion, and related data management system; urban public safety risk index based on big data analysis; rapid emergency decision-making model based on uncertain information; comprehensive situation analysis of urban public security and visualization of time-space coupling Technology. At the end it will be discussed how the project will build a demonstration platform for urban public safety risk prevention and control with integrated monitoring, intelligent early warning, multi-information integration, and integrated management and control. The platform is forming multi-level application demonstrations in municipal level, district level, street level and community level. We expect that the smooth implementation of this project will significantly enhance the intelligent and professional level of public safety governance, promote public safety management system innovation, and safety culture shaping, and provide a "Shenzhen Model" for China in the creation of a safety and smart city.