Towards Trustworthy Autonomous Systems : Taxonomies and Future Perspectives

• The class of Trustworthy Autonomous Systems (TAS) includes cyber-physical systems leveraging on self-x technologies that make them capable to learn, adapt to changes, and reason under uncertainties in possibly critical applications and evolving environments. In the last decade, there has been a growing interest in enabling artificial intelligence technologies, such as advanced machine learning, new threats, such as adversarial attacks, and certification challenges, due to the lack of sufficient explainability. However, in order to be trustworthy, those systems also need to be dependable, secure, and resilient according to well-established taxonomies, methodologies, and tools. Therefore, several aspects need to be addressed for TAS, ranging from proper taxonomic classification to the identification of research opportunities and challenges. Given such a context, in this paper address relevant taxonomies and research perspectives in the field of TAS. We start from basic definitions and move towards future perspectives, regulations, and emerging technologies supporting development and operation of TAS.

Ämnesord

NATURVETENSKAP  -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)

NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Sciences (hsv//eng)

Nyckelord

Taxonomy

Resilience

Computer security

Unified modeling language

Analytical models

Safety

Trustworthy autonomous systems

dependability

cyber-resilience

cybersecurity

artificial intelligence

intelligent systems

Publikations- och innehållstyp

ref (ämneskategori)

art (ämneskategori)