This collection encompasses research and advancements in intrusion detection systems (IDS) focusing on a variety of environments, including networks and the Internet of Things (IoT). The topics range from innovative machine learning techniques, feature selection algorithms, and hybrid models to address challenges like false positives and detection accuracy. The studies highlight the integration of novel approaches, such as ensemble learning and the use of genetic algorithms, to enhance performance in identifying and mitigating cyber threats effectively.