Enhancing IoT network security: a literature review of intrusion detection systems and their adaptability to emerging threats
Bara Fteiha, Huma Zia, Mai Zeyadeh, Raneem Abu Hazeem, Heba Obaidat, Rawan Ghannam · Open Computer Science · 2025
Abstract With the continuous evolution of smart environments powered by Internet of Things (IoT) networks and smart devices, there becomes a crucial need to address and ensure privacy and security. Intrusion Detection Systems (IDSs) that are specially designed for use in IoT networks play a vital role in strengthening the security posture of an IoT network and system by safeguarding and preventing attacks against smart environments. This research paper presents a comparative study of IDSs for IoT networks, with a focus on signature-based, anomaly-based, and specification-based IDS detection methods while highlighting the significance of IDSs in protecting IoT networks and smart environments, which have become recent targets for attackers due to their integration with modern and advanced technologies and their involvement with large volumes of data. The study investigates the mentioned IDS methods covering the strengths and weaknesses of each method in safeguarding smart environments and networks. This paper dives into the characteristics that make IDS decision-making more effective primarily in terms of security, considering privacy and performance. The findings of this study contribute to the hardening of IoT network security by offering recommendations for IDS selection for enhancing IoT overall security, specifically through the adoption of adaptive-based IDSs.