Biblio

The usage of connected devices and their role within our daily- and business life gains more and more impact. In addition, various derivations of Cyber-Physical Systems (CPS) reach new business fields, like smart healthcare or Industry 4.0. Although these systems do bring many advantages for users by extending the overall functionality of existing systems, they come with several challenges, especially for system engineers and architects. One key challenge consists in achieving a sufficiently high level of security within the CPS environment, as sensitive data or safety-critical functions are often integral parts of CPS. Being system of systems (SoS), CPS complexity, unpredictability and heterogeneity complicate analyzing the overall level of security, as well as providing a way to detect ongoing attacks. Usually, security metrics and frameworks provide an effective tool to measure the level of security of a given component or system. Although several comprehensive surveys exist, an assessment of the effectiveness of the existing solutions for CPS environments is insufficiently investigated in literature. In this work, we address this gap by benchmarking a carefully selected variety of existing security metrics in terms of their usability for CPS. Accordingly, we pinpoint critical CPS challenges and qualitatively assess the effectiveness of the existing metrics for CPS systems.

The emergence of Industrial Cyber-Physical Systems (ICPS) in today's business world is still steadily progressing to new dimensions. Although they bring many new advantages to business processes and enable automation and a wider range of service capability, they also propose a variety of new challenges. One major challenge, which is introduced by such System-of-Systems (SoS), lies in the security aspect. As security may not have had that significant role in traditional embedded system engineering, a generic way to measure the level of security within an ICPS would provide a significant benefit for system engineers and involved stakeholders. Even though many security metrics and frameworks exist, most of them insufficiently consider an SoS context and the challenges of such environments. Therefore, we aim to define a security metric for ICPS, which measures the level of security during the system design, tests, and integration as well as at runtime. For this, we try to focus on a semantic point of view, which on one hand has not been considered in security metric definitions yet, and on the other hand allows us to handle the complexity of SoS architectures. Furthermore, our approach allows combining the critical characteristics of an ICPS, like uncertainty, required reliability, multi-criticality and safety aspects.

Implementations of Cyber-Physical Systems (CPS), like the Internet of Things, Smart Factories or Smart Grid gain more and more impact in their fields of application, as they extend the functionality and quality of the offered services significantly. However, the coupling of safety-critical embedded systems and services of the cyber-space domain introduce many new challenges for system engineers. Especially, the goal to achieve a high level of security throughout CPS presents a major challenge. However, it is necessary to develop and deploy secure CPS, as vulnerabilities and threats may lead to a non- or maliciously modified functionality of the CPS. This could ultimately cause harm to life of involved actors, or at least sensitive information can be leaked or lost. Therefore, it is essential that system engineers are aware of the level of security of the deployed CPS. For this purpose, security metrics and security evaluation frameworks can be utilized, as they are able to quantitatively express security, based on different measurements and rules. However, existing security scoring solutions may not be able to generate accurate security scores for CPS, as they insufficiently consider the typical CPS characteristics, like the communication of heterogeneous systems of physical- and cyber-space domain in an unpredictable manner. Therefore, we propose a security analysis framework, called Security Qualification Matrix (SQM). The SQM is capable to analyses multiple attacks on a System-of-Systems level simultaneously. With this approach, dependencies, potential side effects and the impact of mitigation concepts can quickly be identified and evaluated.