Watching against the Unseen: AI-powered Approach to Detect Attacks on Critical Infrastructure
SpliTech 2023 - IEEE International Conference on Smart and Sustainable Technologies - -2023
, Pazienza Andrea, Abbatecola Agostino, Lella Eufemia, Macchiarulo Nicola, Noviello Pietro
In the current research, a safety allocation technique named the Critical Risks Method (CRM) has been developed. Starting from a literature review, we analyzed the shortcomings of conventional methods. The outcomes show the primary two criticalities of the most important safety allocation approaches: (1) They are developed for series configuration, but not for parallel ones; (2) they ordinarily give only qualitative outputs, but not quantitative ones. Moreover, by applying the conventional methods, an increase in safety of the units to ensure the safety target leads to an increase of the production costs of the units. The proposed strategy can overcome the shortcomings of traditional techniques with a safety approach useful to series–parallel systems in order to obtain quantitative outputs in terms of failures in a year. The CRM considers six factors that are able to ensure its applicability to a great variety of critical infrastructures. In addition, CRM is described by a simply analytic definition. The CRM was applied to a critical infrastructure (Liquid Nitrogen Cooling Installation) in a nuclear plant designed with series–parallel units. By comparing the CRM outputs with databank safety values, the proposed method was validated.
author = "Lof\`u, Domenico and Pazienza, Andrea and Abbatecola, Agostino and Lella, Eufemia and Macchiarulo, Nicola and Noviello, Pietro",
title = "Watching against the Unseen: AI-powered Approach to Detect Attacks on Critical Infrastructure",
journal = "SpliTech 2023 - IEEE International Conference on Smart and Sustainable Technologies",
year = "2023",
url = "http://sisinflab.poliba.it/Publications/2023/LPALMN23"