AI-Based Solutions for Security and Resource Optimization in IoT Environments: A Systematic Review

Abstract

Nowadays, the rapid expansion of Internet of Things (IoT) systems has introduced significant challenges related to system management, especially in cybersecurity and resource efficiency areas. This systematic review investigates how AI/ML techniques are being applied to address these challenges, with a particular focus on intrusion detection systems, anomaly detection, and intelligent resource allocation. Using a structured methodology inspired by the PRISMA technique, relevant research articles published between 2018 and 2025 across important databases, including IEEE Xplore, ScienceDirect, SpringerLink, ResearchGate, and Web of Science, were analyzed and compared. The selected studies demonstrate that integrating granular perspectives in AI/ML-based solutions could enhance the resilience of IoT systems. This comprehensive review showed extremely interesting results for AI contributions in real life as well as potential advancements in this area by combining different perspectives in order to improve the security and efficiency of IoT systems.