Integration of Cybersecurity, AI, and IoT Technologies

A special issue of Systems (ISSN 2079-8954).

Deadline for manuscript submissions: 15 August 2025 | Viewed by 1102

Special Issue Editor


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Guest Editor
Département des Sciences Administratives, Université du Québec en Outaouais, 101 Saint-Jean-Bosco, Gatineau, QC J8X 3X7, Canada
Interests: information systems; information technology management; business technology management; digital transformation; project management; risk analytics; semantic technologies

Special Issue Information

Dear Colleagues,

Recent literature reviews have pointed out the intersection of Cybersecurity, Artificial Intelligence (AI), and Internet of Things (IoT) as the new “nexus” of our digital experience. The same way “web browsers” and “smart phones” have been our main interfaces, AI coupled with IoT, or AIoT, will soon become our new locus. This Special Issue will showcase contributions that address this intersection; we welcome articles throughout the spectrum of academic research: literature reviews, conceptual frameworks, methodological notes, empirical research, standards development, and implementation reviews. Cross-sectors and sector-specific studies (e.g., energy, healthcare, cities, etc.) are welcomed. Nevertheless, conclusions should attempt to generalize to various or all sectors, addressing at least one or two major gaps identified by recent reviews, including (but not limited to) the following:

  • Enterprise cybersecurity prevention within the AIoT sphere;
  • Cybersecurity incident response automation for AIoT end-users;
  • Humans and ethics in the loop for the regulatory compliance of AIoT systems;
  • Design methods for ensuring explainable AIoT implementations;
  • Small-footprint machine learning algorithms for AIoT applications;
  • Large language model consumption in small AIoT devices;
  • Algorithmic safety and privacy control in AIoT environments;
  • App stores and global AIoT entrepreneurial ecosystems;
  • National development strategies for cybersecurity and AIoT ecosystems.

Dr. Stephane Gagnon
Guest Editor

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Keywords

  • cybersecurity
  • Artificial Intelligence (AI)
  • Internet of Things (IoT)
  • AIoT systems
  • enterprise cybersecurity

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Published Papers (1 paper)

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Research

39 pages, 12160 KiB  
Article
Digital Health Transformation: Leveraging a Knowledge Graph Reasoning Framework and Conversational Agents for Enhanced Knowledge Management
by Abid Ali Fareedi, Muhammad Ismail, Stephane Gagnon, Ahmad Ghazanweh and Zartashia Arooj
Systems 2025, 13(2), 72; https://doi.org/10.3390/systems13020072 - 22 Jan 2025
Viewed by 409
Abstract
The research focuses on the limitations of traditional systems in optimizing information flow in the healthcare domain. It focuses on integrating knowledge graphs (KGs) and utilizing AI-powered applications, specifically conversational agents (CAs), particularly during peak operational hours in emergency departments (EDs). Leveraging the [...] Read more.
The research focuses on the limitations of traditional systems in optimizing information flow in the healthcare domain. It focuses on integrating knowledge graphs (KGs) and utilizing AI-powered applications, specifically conversational agents (CAs), particularly during peak operational hours in emergency departments (EDs). Leveraging the Cross Industry Standard Process for Data Mining (CRISP-DM) framework, the authors tailored a customized methodology, CRISP-knowledge graph (CRISP-KG), designed to harness KGs for constructing an intelligent knowledge base (KB) for CAs. This KG augmentation empowers CAs with advanced reasoning, knowledge management, and context awareness abilities. We utilized a hybrid method integrating a participatory design collaborative methodology (CM) and Methontology to construct a domain-centric robust formal ontological model depicting and mapping information flow during peak hours in EDs. The ultimate objective is to empower CAs with intelligent KBs, enabling seamless interaction with end users and enhancing the quality of care within EDs. The authors leveraged semantic web rule language (SWRL) to enhance inferencing capabilities within the KG framework further, facilitating efficient information management for assisting healthcare practitioners and patients. This innovative assistive solution helps efficiently manage information flow and information provision during peak hours. It also leads to better care outcomes and streamlined workflows within EDs. Full article
(This article belongs to the Special Issue Integration of Cybersecurity, AI, and IoT Technologies)
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