IoT and Man‐in‐the‐Middle Attacks

ABSTRACT This article provides an overview of the Internet of things (IoT) and its growing significance in today's interconnected world. It discusses the concept of man‐in‐the‐middle (MitM) attacks in detail, including their various types, causes, and potential impacts on IoT networks. The article analyzes MitM attacks at different layers of the IoT architecture and explores current prevention techniques and mitigation strategies. It addresses the challenges in detecting and preventing such attacks, particularly in the context of the heterogeneous and resource‐constrained nature of IoT devices. The article also examines emerging technologies, such as machine learning and blockchain, for enhancing IoT security. Furthermore, it discusses open issues, including the challenges of prevention, the potential impact of new technologies, and future trends in MitM attacks. By exploring these aspects, the article aims to provide insights into improving detection and prevention mechanisms against MitM attacks in IoT environments.

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Institutions

Publication Details

Journal
Security and Privacy
Published
2025-03-01
DOI
https://doi.org/10.1002/spy2.70016
Citations
30
Primary Topic
Network Security and Intrusion Detection
Type
article
Field-Weighted Citation Impact
44.61
Controls
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article

IoT and Man‐in‐the‐Middle Attacks

Hamidreza Fereidouni, Olga Fadeitcheva, Mehdi Zalai
30 citations
Security and Privacy
Network Security and Intrusion Detection
44.61
article

IoT and Man‐in‐the‐Middle Attacks

Hamidreza Fereidouni, Olga Fadeitcheva, Mehdi Zalai
article en
30 citations

Abstract

ABSTRACT This article provides an overview of the Internet of things (IoT) and its growing significance in today's interconnected world. It discusses the concept of man‐in‐the‐middle (MitM) attacks in detail, including their various types, causes, and potential impacts on IoT networks. The article analyzes MitM attacks at different layers of the IoT architecture and explores current prevention techniques and mitigation strategies. It addresses the challenges in detecting and preventing such attacks, particularly in the context of the heterogeneous and resource‐constrained nature of IoT devices. The article also examines emerging technologies, such as machine learning and blockchain, for enhancing IoT security. Furthermore, it discusses open issues, including the challenges of prevention, the potential impact of new technologies, and future trends in MitM attacks. By exploring these aspects, the article aims to provide insights into improving detection and prevention mechanisms against MitM attacks in IoT environments.

Security and PrivacyVol. 8(2)
Polytechnique Montréal (CA), Université de Montréal (CA)
Openalex Percentile: Top 0%
Network Security and Intrusion Detection
44.61
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