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.
Speech Title: Remote Testing and Integration in Intelligent Manufacturing
Abstract: Concurrent, distributive and intelligent environment is essential for intelligent manufacturing of complex systems in their operational software design, testing and maintenance due to the exponential rise in their complexity. The Internet and related technologies offer significant new capabilities, which enable experts to remotely design, test, and maintain Internet-enabled operational software for complex systems. The obvious benefit of this approach is to allow multiple design teams working together on a common task over the Internet without recognizing the geographical separation and therefore time to market for complex systems is reduced. Also it allows software designers to trace and maintain their products without the need of conducting on-site maintenance. This presentation reports the research results obtained in dealing with the challenges below:
How to remotely monitor the performance of the operational software and maintain their behaviour at an acceptable level.
Prof. Yulin Wang is a full professor and PhD supervisor
in International School of Software, Wuhan University,
China. He got PhD degree in 2005 in Queen Mary,
University of London, UK. Before that, he has worked in
high-tech industry for more than ten years. He has
involved many key projects, and hold 8 patents. He got
his master and bachelor degree in 1990 and 1987
respectively from Xi-Dian University, and Huazhong
University of Science and Technology(HUST), both in
China. His research interests include digital rights
management, digital watermarking, multimedia and network
security, and signal processing. In recently 10 years,
Prof. Wang has published as first author 3 books, 40
conference papers and 45 journal papers, including in
IEEE Transactions and IEE proceedings and Elsevier
Journals. Prof. Wang served as editor-in-chief for
International Journal of Advances in Multimedia in 2010.
He served as reviewer for many journals, including IEEE
Transactions on Image Processing, IEEE Signal Processing
Letters, Elsevier Journal of Information Sciences. He
served as reviewer for many research funds, including
National High Technology Research and Development
Program of China ( ‘863’ project). Prof. Wang was the
external PhD adviser of Dublin City University, Ireland
during 2008-2010. He was the keynote speakers in many
international conferences. He bas been listed in Marcus
‘who’s who in the world’ since 2008.
Speech Title: Detection of Software Source Code Clone
Absteact: Code clones are separate fragments of code that are very similar. They are a common phenomenon in an application that has been under development for some time. Although modern programming languages offer various abstraction mechanisms to facilitate reuse of code fragments, copy-paste is still a widely used reuse strategy. This often leads to numerous duplicated code fragments -so called clones- in large software systems. However, cloning is problematic for software maintenance for several reasons:
(1) Cloning unnecessarily increases program size. Since many maintenance efforts correlate with program size, this increases the maintenance effort.
(2) Changes to one clone, such as bug fixing, typically need to be made to the other clones as well, again increasing maintenance effort.
(3) If changes to duplicated source code fragments are performed inconsistently, this can introduce bugs.
In this talk, we begin with background concepts, a generic clone detection process and an overall taxonomy of current techniques and tools. We then classify, compare and evaluate the techniques and tools in two different dimensions. First, we classify and compare approaches based on a number of facets, each of which has a set of (possibly overlapping) attributes. Second, we qualitatively evaluate the classified techniques and tools with respect to a taxonomy of editing scenarios.
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.
Speech Title: A Multiple Perspective Approach for Insider Threat Risk Prediction in Cyber-Security
Abstract: With the use of the dark web, leaking and selling of mass data have become easier. The approach of looking into insider security threats from the multiple perspectives has been proposed: human issue, technology factor, and organization aspect are together considered to form the solution for risk prediction. In this keynote, we will first review case studies of insider crimes from the seven categories: 1) insider IT sabotage, 2) insider IT fraud, 3) insider theft of intellectual property, 4) insider social engineering, 5) unintentional insider threat incident, 6) insider in cloud computing, and 7) insider national security, in order to understand how authorized users could harm their organizations. Then a novel approach to predict malicious insider threats before the breach takes place will be discussed. Bayesian network statistical methods are used to implement and test the proposed model by using the collected real data from an organization.
Verification is conducted for the prediction model in comparison with the output of 61 cases from an education sector and shows a good consistence. The correlation in the results is around R2 =0.87 indicating the acceptance fit of this area of the research. From the results we expected that the approach will be useful for security experts. It not only provides organizations with an insider threat risk assessment tool, but also helps organizations discover their weakness for which more attention is needed in dealing with insider threats. Moreover, we expect the model to be useful to the researcher’s community as the basis for understanding and future research.