Artificial Intelligence in Cybersecurity: Activities of the CINI-AIIS Lab at University of Naples Federico II

Integrating Information and Communication Technologies in industrial environments has transformed traditional industrial plant into Cyber-Physical Systems (CPSs), thereby expanding their vulnerability to cyber-attacks with potentially severe consequences. This paper presents the research activities of the CINI-AIIS Laboratory at the University of Naples Federico II targeting the challenge of anomaly detection in CPSs. Our study also presents an empirical evaluation of unsupervised deep learning techniques trained on either sensor/actuator or network traffic data, tested on synchronized real-world CPS datasets. These research activities underscore the importance of multimodal data integration in advancing cyber-security for critical infrastructures.