This Thematic Track is a well-established track within QUATIC, where researchers, developers, testers, and users from industry get together to present and discuss the most recent innovations, experiences and open challenges related to safety and security & privacy aspects of complex software systems.
Indeed, these aspects are increasingly important as more and more software is embedded into our homes, cars, trains and also, many relevant vital systems for critical infrastructures are moving towards the cloud. Developers have to consider safety, security & privacy requirements in the whole system and applications lifecycle, from design to operation and new methodologies and techniques are needed.
The authors are invited to submit research results as well as practical experiment or project reports. Industrial papers about applications or case studies are also welcomed in different domains (e.g., telemedicine, critical infrastructures, mobile networks, embedded applications, etc.).Â
The topics of interest include, but are not limited to:
Software safety and risk management
Software safety regulations and standardsÂ
Agile development in safety-critical software systems
Methods and tools in safety-critical software systems
Quality metrics for safety and securityÂ
Security models and security policies
Security testing and monitoring
Cloud, IoT and Big Data security
Attacks tolerance and resilience
Security and risk assesment
Distributed systems security
SLAs for safety, security and privacy
Privacy
Case studies
Chairs: Triet Le (University of Adelaide, Australia), TBA
Program Committee:Â
TBA
Triet Le, Adelaide University, Australia
Triet Le is a Lecturer, a.k.a. Assistant Professor, in the School of Computer Science and Information Technology at Adelaide University, formerly The University of Adelaide. He leads the Software Security Intelligence research at the Centre for Research on Engineering Software Technologies (CREST). He obtained his Ph.D. from the University of Adelaide. His research interests include Mining Software Repositories and Software Security, particularly in software vulnerability analytics. His research focuses on providing automation and knowledge support for software vulnerability assessment using data-driven approaches based on Large Language Models, Machine Learning, Deep Learning, and Natural Language Processing. He has published in top-quality (ICORE A/A*) venues, such as International Conference on Software Engineering (ICSE), International Conference on Automated Software Engineering (ASE), ACM Computing Surveys (CSUR), International Conference on Mining Software Repositories (MSR), International Conference on Software Maintaince and Evolution (ICSME), and International Conference on Evaluation and Assessment in Software Engineering (EASE). He has also served as a PC member for the ICSE, SANER, and MSR conferences and received the Distinguished Reviewer Award at MSR 2022.