Dr. Mario LaManna received the degree in Electronic Engineering (summa cum laude) from the University of Pisa, Italy. He is working with EVOELECTRONICS in Rome, Italy as Senior Scientist and Project Leader. He has taken part in a number of projects in the fields of defense and security. He is leader of a number of international cooperative projects and has participated in more than 100 international conferences as paper author, session chairman and forum moderator. He is a Member of the IEEE and IIIS and a CapTech Expert of the EDA IAP02 (Sensor Systems).

Critical infrastructure protection faces increasing challenges, both in quality and in quantity. Most of the present security systems fully rely on automated mechanisms, which replace human operators, in order to perform computation intensive tasks and/or to work in extreme conditions. However, this solution presents some drawbacks with respect to the system performance. In order to provide effective measures against the pressure of new and sophisticated threats, an interdisciplinary approach, based on suitably coupling machine learning with human judgment, results as the right choice. In fact, this solution is particularly helpful for implementing efficient solutions capable of controlling critical scenarios and reacting effectively towards sophisticated threats. The practical application of this approach in different case studies demonstrates its efficiency for the effective protection of critical infrastructures.