Increasing interdependencies between critical infrastructures and digitization increase the vulnerability to cyber-attacks and cyber-physical attacks. Incidents have multiple direct and indirect consequences, including cascading effects, and a formal analysis is strongly recommended to understand these effects. This paper shows how threat identification and impact evaluation for interdependent critical infrastructures can be supported by two existing tools. The approach is illustrated with an example based on a running EU project.

Probabilistic risk models are popular due to their ability to capture uncertainty. However, the parametrization of such models may be challenging, especially in the context of critical infrastructures where data is sometimes sparse. In this paper we propose different methods to parametrize a stochastic model of risk propagation depending on the amount of information available. Two of the approaches are illustrated with an example of a critical infrastructure and the application of the other methods is sketched.

Modern automobiles are considered semi-autonomous vehicles regarding new adaptive technologies. New cars consist of a vast number of electronic units for managing and controlling the functional safety in a vehicle. In the vehicular industry, safety and security are considered two sides for the same coin. Therefore, improving functional safety in the vehicular industry is essential to protect the vehicle from different attack scenarios. This work introduces an ontology-based model for security verification and validation in the vehicular domain. The model performs a series of logical quires and inference rules to ensure that the security requirements are fulfilled. It endeavors to enhance the current security state of a vehicle by selecting additional security requirements that can handle existence security weaknesses and meet the actual security goal.

Internet technology has changed how people work, live, communicate, learn and entertain. The internet adoption is rising rapidly, thus creating a new industrial revolution named "Industry 4.0". Industry 4.0 is the use of automation and data transfer in manufacturing technologies. It fosters several technological concepts, one of these is the Internet of Things (IoT). IoT technology is based on a big network of machines, objects, or people called "things" interacting together to achieve a common goal. These things are continuously generating vast amounts of data. Data understanding, processing, securing and storing are significant challenges in the IoT technology which restricts its development. This paper presents a new reference IoT model for future smart IoT solutions called Cloud Web of Things (CloudWoT). CloudWoT aims to overcome these limitations by combining IoT with edge computing, semantic web, and cloud computing. Additionally, this work is concerned with the security issues which threatens data in IoT application domains.