Analysing Behavioural Risks of Self-Adaptive Software Systems.

Prof. Yijun Yu, The Open University, UK

Friday October 20th, 2017, 2:00pm.
1004DB (Victor Philip Dardaleh Building)

Security and privacy concerns often involve two perspectives. Attackers would exploit system vulnerabilities to increase the likelihood of success in attacking assets (e.g., the system or people); Defenders would protect assets to minimise the likelihood of being attacked and the loss. These lead to different risk calculations. To quantify these risks, we alternate between the protecting and attacking perspectives as part of an iterative process for self-adaption.

About the Speaker. Dr. Yijun Yu is a Senior Lecturer in Computing at The Open University, UK. He is interested in developing automated, efficient and scalable software techniques and tools to better support human activities in software engineering. He has a vision to improve aviation security through cloud computing and blockchains by live streaming blackboxes, which was featured in interviews with BBC after the missing MH370 flight, and subsequently received a Microsoft Azure Award (2017). His research on Requirements-driven Self-Adaptation receives a 10 Year Most Influential Paper award (CASCON’16), 5 Best Paper awards and 3 Distinguished Paper awards.

This is a joint work with many colleagues the The Open University (Bashar Nuseibeh, Michael Jackson, Thein Than Tun, Amel Bennaceur, Arosha Bandara, Blaine Price, and Andrea Zisman), inspired by my international collaborators from Canada (Sotirios Liaskos, Alexei Lapouchnian, Eric Yu, John Mylopoulos), Japan (Zhenjiang Hu, Nobukazu Yoshioka), Qatar (Armstrong Nhlabatsi, Khaled Khan), and China (Xin Peng, Bihuan Chen, Chun Liu, Wei Liu). It is sponsored by research projects on Secure Adaptive and Usable Software Engineering (EPSRC Platform, 2018-2022), Adaptive Security and Privacy (ERC Adv. Grant, 2012-2018), Adaptive Information Systems (QNRF, 2012-2016), Lifelong Security Engineering for Evolving Systems (EU FP7, 2009-2012), and Usable Privacy for Mobile Apps (Microsoft SEIF, 2012).