The entropy-oriented approach called security- or cybersecurity-informed safety (SIS or CSIS, respectively) is discussed and developed in order to analyse and evaluate the safety and dependability of autonomous transport systems (ATSs) such as unmanned aerial vehicles (UAVs), unmanned maritime vehicles (UMVs), and satellites. This approach allows for extending and integrating the known techniques FMECA (Failure Modes, Effects, and Criticality Analysis) and IMECA (Intrusion MECA), as well as developing the new SISMECA (SIS-based Intrusion Modes, Effects, and Criticality Analysis) technique. The ontology model and templates for SISMECA implementation are suggested. The methodology of safety assessment is based on (i) the application and enhancement of SISMECA considering the particularities of various ATSs and roles of actors (regulators, developers, operators, customers); (ii) the development of a set of scenarios describing the operation of ATS in conditions of cyberattacks and physical influences; (iii) AI contribution to system protection for the analysed domains; (iv) scenario-based development and analysis of user stories related to different cyber-attacks, as well as ways to protect ATSs from them via AI means/platforms; (v) profiling of AI platform requirements by use of characteristics based on AI quality model, risk-based assessment of cyberattack criticality, and efficiency of countermeasures which actors can implement. Examples of the application of SISMECA assessment are presented and discussed.

Technological advances in modern Train Control Systems (TCSs) promise to improve dependability of railway transportation in terms of safety, availability, and capacity, notably by employing novel distancing policies such as Moving Block (MB) signaling and Virtual Coupling (VC), fueled by advanced train localization methods such as satellite positioning. At the same time, these technological advances raise notable concerns about the effects that uncertainty in critical TCS parameters (such as train position and speed) may have on dependability-related attributes. Recently, various approaches have been proposed to characterize such effects through quantitative measures, leveraging formal stochastic modeling and evaluation of the TCS behavior. In this paper, we illustrate the results of a systematic review of the literature on quantitative evaluation of dependability-related attributes of TCSs under uncertainty on vital parameters. Specifically, we have finally selected 42 relevant papers, published between 2011 and 2023, that succeed in giving, through an empirical perspective and classification, a comprehensive view of current research and practice in quantitative dependability assessment of TCSs.