Assessing the Suitability of IoT Security Datasets for IDS
Manasa Koppula, L. M. I. Leo Joseph · 2025
This chapter highlights the growing urgency for robust Intrusion Detection Systems (IDS) in the Internet of Things (IoT) security, focusing on sustainable cybersecurity strategies within the modern, highly interconnected digital ecosystem. As the rapid expansion of IoT devices presents vast attack surfaces, it is crucial to develop IDS that protect interconnected environments. This chapter performs a thorough analysis of IDS detection mechanisms and IoT security datasets, critically assessing the relevance and reliability. The evaluation emphasizes essential dataset attributes, including source authenticity, diversity, data volume, and real-world applicability. By systematically analyzing these criteria, the paper identifies datasets that offer comprehensive insights into IoT security's challenges, offering researchers a detailed resource for selecting datasets that align with the complexity of current IDS development. This review thus serves as a foundational guide for advancing IDS technology, aiming to foster more resilient and adaptive security solutions within the IoT landscape.