Smart devices have become widespread and used in critical situations. It is predicted that 20 billion smart devices will be connected to the Internet by 2020, creating the Internet of Things (IoT) and providing higher-level services in e.g. smart homes, smart buildings, smart energy, smart cars, smart transportation, and smart cities. Furthermore, critical infrastructures are dependent on Information Communication and Technology due to digitalization.
The boundary between critical infrastructures and ordinary smart consumer devices has faded and their interconnection has created systems-of-systems (SoS) that synergistically interact to form new and intelligent services. There are many risks and challenges to critical societal infrastructures faced by SoS such as: (1) Potential for change in the system(s) from multiple directions: stakeholders, constituent systems as well as evolving business requirements; (2) Less predictability regarding stakeholders’ needs, technology advances, and component behavior typical in an environment with no central control; (3) Failures with cause or impact (cascade) beyond the individual system boundary; (4) Constraints in terms of new development and evolution because of existing collection of design choices; and (5) Limited knowledge of individual system state and behavior.
The goal of this PhD project is to explore data-driven approaches to reduce security risks during architectural decision-making for SoS-like smart systems. Eliciting security risks of architectural and design elements during architectural decision-making is a challenging and complex process that requires input from many heterogeneous sources. The PhD candidate will investigate and design a distributed data-driven middleware framework to support security risks elicitation and mitigation when joining or designing a new SoS-like system. The task will involve the modelling of both structured and unstructured information sources and integrating them in the framework. Aspects of the investigation will also involve empirical studies of types of SoS (directed, acknowledged, virtual, or collaborative) and security defect prediction for each type.
Deadline: 30th July, 2020
Working place: Bergen, Norway
Salary: 479.000 NOK per year
Detail information at: https://www.jobbnorge.no/en/available-jobs/job/188850/phd-research-fellow-in-secure-data-driven-architecture-for-smart-systems-of-systems