A Bibliometric Review of Intrusion Detection Research in IoT: Evolution, Collaboration, and Emerging Trends

Abstract

As the IoT market continues to rapidly expand, ensuring the security of IoT systems becomes increasingly critical. This paper aims to identify emerging trends and technologies in IoT intrusion detection. A bibliometric analysis of research trends in IoT intrusion detection, leveraging data from the Web of Science (WoS) repository, is conducted to understand the landscape of publications in this field. The analysis reveals a significant increase in publications on intrusion detection in IoT, indicating growing research interest. Research articles are the leading category of publications, and the analysis also highlights the collaborative linkages among authors, institutions, and nations. Co-occurrence analysis and citation analysis provide insights into the relationships among keywords and the impact of publications. The study also identifies keyword and publication citation burst detection, with recommendations for future research focusing on advanced machine learning techniques to enhance intrusion/anomaly detection. This comprehensive analysis offers valuable guidance for diverse and extensive applications in IoT intrusion detection.