Audit of IoT networks: assessing vulnerabilities and protecting against cyber attacks

This article addresses current challenges in ensuring security within the Internet of Things (IoT) networks, taking into account the modern challenges of the digital transformation era. The key risks associated with the use of IoT devices are outlined: the limitations of built-in security mechanisms, the lack of unified standards, hardware resource constraints, and the complexity of managing heterogeneous environments. Special attention is given to the role of security auditing as a tool for identifying vulnerabilities, assessing risks, and developing strategies to counter cyber threats. Existing auditing approaches, including reactive (retroactive), proactive, and incremental methods, are analyzed in the context of IoT environments. A comparative analysis of IoT system architectures—centralized, decentralized, and hybrid—is provided, highlighting their impact on security. A test model of an IoT network is proposed for practical threat modeling and auditing procedure verification. The article also focuses on modern risk management methodologies, including: ISO/IEC 27005, NIST RMF, OCTAVE, EBIOS, FAIR, COBIT, and CRAMM. The advantages and disadvantages of each are discussed in the context of IoT, emphasizing the suitability of the EBIOS methodology as the most adaptable for complex hybrid systems. The article also stresses the need for the improvement of security policies, adaptation of standards, and the development of auditing procedures that address both technical and organizational aspects of IoT operations. The main goal is to contribute to the creation of a reliable, scalable, and threat-resistant IoT ecosystem.

Authors

Publication Details

Journal
TECHNICAL SCIENCES AND TECHNOLOGIES
Published
2025-05-22
DOI
https://doi.org/10.25140/2411-5363-2025-1(39)-170-183
Citations
1
Primary Topic
Network Security and Intrusion Detection
Type
article
Field-Weighted Citation Impact
1.49
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Audit of IoT networks: assessing vulnerabilities and protecting against cyber attacks

Yuriy Pidlisnyi
1 citations
TECHNICAL SCIENCES AND TECHNOLOGIES
Network Security and Intrusion Detection
1.49
article

Audit of IoT networks: assessing vulnerabilities and protecting against cyber attacks

Yuriy Pidlisnyi
article en
1 citations

Abstract

This article addresses current challenges in ensuring security within the Internet of Things (IoT) networks, taking into account the modern challenges of the digital transformation era. The key risks associated with the use of IoT devices are outlined: the limitations of built-in security mechanisms, the lack of unified standards, hardware resource constraints, and the complexity of managing heterogeneous environments. Special attention is given to the role of security auditing as a tool for identifying vulnerabilities, assessing risks, and developing strategies to counter cyber threats. Existing auditing approaches, including reactive (retroactive), proactive, and incremental methods, are analyzed in the context of IoT environments. A comparative analysis of IoT system architectures—centralized, decentralized, and hybrid—is provided, highlighting their impact on security. A test model of an IoT network is proposed for practical threat modeling and auditing procedure verification. The article also focuses on modern risk management methodologies, including: ISO/IEC 27005, NIST RMF, OCTAVE, EBIOS, FAIR, COBIT, and CRAMM. The advantages and disadvantages of each are discussed in the context of IoT, emphasizing the suitability of the EBIOS methodology as the most adaptable for complex hybrid systems. The article also stresses the need for the improvement of security policies, adaptation of standards, and the development of auditing procedures that address both technical and organizational aspects of IoT operations. The main goal is to contribute to the creation of a reliable, scalable, and threat-resistant IoT ecosystem.

TECHNICAL SCIENCES AND TECHNOLOGIES(1 (39))
Openalex Percentile: Top 17%
Network Security and Intrusion Detection
1.49
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.