AI-driven Access Control System for Smart Factory Devices
Year: 2025
Type: conference-paper
Abstract: The authors of the article examined the modern challenges involved in developing an access control system for smart factories, focusing on the creation of an integrated solution for monitoring and managing the information security of the Internet of Things (loT) through the integration of diverse tools and methods within a single system. In this paper, the information system is examined through the lens of system analysis, focusing on the interactions between the subjects and objects within the system. This perspective allows for an accurate assessment of the current state of obj ects, taking into account the system's architecture and its vulnerabilities, as well as the evolution of the system state over time. The approach proposed incorporates modern tools and software solutions, including intrusion detection systems (IDS), fuzzy testing, Software Bill of Materials (SBOM), and various machine learning (ML) techniques.
Authors: Oleh V. Zaritskyi, Dmytro Shyrokorad, Rosella Omana Mancilla, J oerg Abendroth, Antonis Mpantis, Oscar Garcia Perales, George Triantafyllou, Armando Aguayo Mendoza RDI, Ravishankar Borgaonkar
Language: English
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Funder: European Commission
OpenAlex ID: W4411995959