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The Forefront of Internet of Things Cybersecurity with Artificial Intelligence

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Internet of Things".

Deadline for manuscript submissions: 25 January 2026 | Viewed by 4312

Special Issue Editor

Special Issue Information

Dear Colleagues,

The rapid expansion of the Internet of things (IoT) has significantly increased the complexity and vulnerability of cybersecurity landscapes. In this Special Issue, we aim to explore the critical role of artificial intelligence (AI) in enhancing the security of IoT ecosystems. We invite research that delves into innovative AI-driven approaches to safeguarding connected devices and networks.

We encourage submissions that address the intersection of IoT cybersecurity and AI, focusing on, but not limited to, the following areas:

  • IoT device security.
  • IoT data privacy.
  • AI-driven anomaly detection in IoT systems.
  • AI techniques for IoT security enhancement.
  • AI-powered risk assessment for IoT environments.
  • AI-enabled threat intelligence in the IoT.

We look forward to contributions that provide new insights and advancements in applying AI technologies to the field of IoT security.

Dr. Shingo Yamaguchi
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • IoT security
  • IoT data privacy
  • AI-powered cyber security

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Published Papers (1 paper)

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Research

40 pages, 695 KiB  
Article
Generative AI and LLMs for Critical Infrastructure Protection: Evaluation Benchmarks, Agentic AI, Challenges, and Opportunities
by Yagmur Yigit, Mohamed Amine Ferrag, Mohamed C. Ghanem, Iqbal H. Sarker, Leandros A. Maglaras, Christos Chrysoulas, Naghmeh Moradpoor, Norbert Tihanyi and Helge Janicke
Sensors 2025, 25(6), 1666; https://doi.org/10.3390/s25061666 - 7 Mar 2025
Viewed by 3843
Abstract
Critical National Infrastructures (CNIs)—including energy grids, water systems, transportation networks, and communication frameworks—are essential to modern society yet face escalating cybersecurity threats. This review paper comprehensively analyzes AI-driven approaches for Critical Infrastructure Protection (CIP). We begin by examining the reliability of CNIs and [...] Read more.
Critical National Infrastructures (CNIs)—including energy grids, water systems, transportation networks, and communication frameworks—are essential to modern society yet face escalating cybersecurity threats. This review paper comprehensively analyzes AI-driven approaches for Critical Infrastructure Protection (CIP). We begin by examining the reliability of CNIs and introduce established benchmarks for evaluating Large Language Models (LLMs) within cybersecurity contexts. Next, we explore core cybersecurity issues, focusing on trust, privacy, resilience, and securability in these vital systems. Building on this foundation, we assess the role of Generative AI and LLMs in enhancing CIP and present insights on applying Agentic AI for proactive defense mechanisms. Finally, we outline future directions to guide the integration of advanced AI methodologies into protecting critical infrastructures. Our paper provides a strategic roadmap for researchers and practitioners committed to fortifying national infrastructures against emerging cyber threats through this synthesis of current challenges, benchmarking strategies, and innovative AI applications. Full article
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