As robotic systems become more integrated into our daily lives, there is growing concern about cybersecurity. Robots used in areas such as autonomous driving, surveillance, surgery, home assistance, and industrial automation can be vulnerable to cyber-attacks, which could have serious real-world consequences. Modern robotic systems face a unique set of threats due to their evolving characteristics. This paper outlines the SESAME project’s methodology for the automated security analysis of multi-robot systems (MRS) and the production of Executable Digital Dependability Identities (EDDIs). Addressing security challenges in MRS involves overcoming complex factors such as increased connectivity, human–robot interactions, and a lack of risk awareness. The proposed methodology encompasses a detailed process, starting from system description and vulnerability identification and moving to the generation of attack trees and security EDDIs. The SESAME security methodology leverages structured repositories like Common Vulnerabilities and Exposures (CVE), Common Weakness Enumeration (CWE), and Common Attack Pattern Enumeration and Classification (CAPEC) to identify potential vulnerabilities and associated attacks. The introduction of Template Attack Trees facilitates modeling potential attacks, helping security experts develop effective mitigation strategies. This approach not only identifies, but also connects, specific vulnerabilities to possible exploits, thereby generating comprehensive security assessments. By merging safety and security assessments, this methodology ensures the overall dependability of MRS, providing a robust framework to mitigate cyber–physical threats.

The growing trend towards the exchange of data between heterogeneous objects and platforms have increased the level of complexity in the Internet of Things (IoT) area. Beyond those, to enable seamless resource sharing between different IoT systems, efforts by academia and industry have currently focused on achieving semantic interoperability between IoT platforms. That involves the delivery of dynamic interaction between platforms to interconnect the variety of smart objects covering both multiple technologies and intelligent services. With this in mind, the main goal of this work is to propose a mechanism to validate and achieve interoperability between IoT platforms. A motivating example is described and analyzed along with the implementation of the proposed system.