AI-driven Access Control System for Smart Factory Devices

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

Institutions

Publication Details

Published
2025-06-16
DOI
https://doi.org/10.1109/smartcomp65954.2025.00084
Citations
1
Primary Topic
Digital Transformation in Industry
Type
article
Field-Weighted Citation Impact
1.24
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

AI-driven Access Control System for Smart Factory Devices

Dmytro Shyrokorad, Ravishankar Borgaonkar, Joerg Abendroth, Oleh Zaritskyi et al.
1 citations
Digital Transformation in Industry
1.24
article

AI-driven Access Control System for Smart Factory Devices

Dmytro Shyrokorad, Ravishankar Borgaonkar, Joerg Abendroth, Oleh Zaritskyi, Rosella Omana Mancilla, Antonis Mpantis
article en
1 citations

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.

National University Zaporizhzhia Polytechnic (UA), SINTEF (NO), Taras Shevchenko National University of Kyiv (UA), Informa (Italy) (IT), Athens Technology Center (Greece) (GR), Nokia (Germany) (DE), University of Stavanger (NO)
Affordable and clean energy
Openalex Percentile: Top 18%
Digital Transformation in Industry
1.24
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.