Advances in Artificial Intelligence (AI) technology have opened up new markets and opportunities for progress in critical areas such as systems and network resiliency, health, education, energy, economic inclusion, social welfare. AI is expected to play an increasing role in defensive and offensive measures to provide a rapid response to react to the landscape of evolving threats.
Traditionally, cyber-physical systems (CPS) security has focused on the detection of attacks in CPS and has been investigated from the perspective of preventing intruders from gaining access to the system using cryptography and other access control techniques. However, in a world of increasing adversaries, it is becoming more difficult to totally prevent CPS from adversarial attacks, hence the need to focus on making CPS resilient.
Resilient CPS is designed to withstand disruptions and remain functional despite the operation of adversaries. One of the dominant methodologies explored for building resilient CPS is dependent on machine learning (ML) algorithms. However, rising from recent research in adversarial ML, requires that ML algorithms for securing CPS must themselves be resilient.
Resilient Artificial Intelligence workshop aims to collect the most recent research trends, advances, and promising future research directions from the international research community in order to take a comprehensive stock on Artificial Intelligence-driven security and resilience approaches, of the interactions among resilient CPS using ML, DL, and resilient AI-based approaches applied in CPS, the recent advances on securing AI for CPS and countermeasures, as well as research trends in this active area, also including the exploration of Adversarial Resilience Learning, as one of the most challenging issue recently investigated by several cyber-security communities.
Prospective authors are encouraged to submit previously unpublished contributions from a broad range of topics, which include but are not limited to the following:
› Artificial Intelligence Driven Resilience
› Resilient Machine and Deep Learning
› Explainable Artificial Intelligence for Resilience
› Metrics for Resilience in Artificial Intelligence
› Adversarial Resilience
› AI Approaches to Trust and Reputation Inference
› Safety and Security in the Future of AI
› Security of deep learning systems
› Robust Decision Making for Security
› Robust Statistics
› Robust Training Methods
› Resilient Distributed
› Secure Federated Learning
› White-box and oracle AI attacks
› AI-Based Cyber Threats
› Malicious AI
Paper submission deadline: April 19, 2021
Authors’ notification: May 3, 2021
Camera-ready submission: May 10, 2021
Early registration deadline: May 31, 2021
Workshop date: July 28, 2021
The workshop’s proceedings will be published by IEEE and will be included in IEEE Xplore. The guidelines for authors, manuscript preparation guidelines, and policies of the IEEE CSR conference are applicable to RAI 2021 workshop. Please visit the authors’ instructions page for more details. When submitting your manuscript via the conference management system, please make sure that the workshop’s track 2T9 RAI is selected in the Topic Areas drop down list.
Pasquale Cantiello, INGV (IT)
Nicole Bussola, FBK (IT)
Giovanni Paragliola, CNR-ICAR (IT)
Laura Verde, CNR-ICAR (IT)
Giacomo Iadarola, CNR-IIT (IT)
Mariangela Graziano, UniCampania (IT)
Sabatino Carbone, Federico II (IT)
Antonio S. Valente, AK-12 (IT)
Carlo Sanghez, GAM (IT)
Salvatore Russo, Meridiana Italia (IT)
Emilio Frusciante (IT)
Michele Mastroianni, UniCampania (IT)
Mauro Iacono, UniCampania (IT)