A Novel Distributed Tree-Based One-Hot Encoding (DTOHE) Technique for Intrusion Detection

In the realm of cloud security, intrusion detection systems (IDSs) play a pivotal role as they are instrumental in identifying vulnerable activities occurring across networks and computer systems. Developing a novel IDS for Internet of Things (IoT)-enabled networks is a complex undertaking beset by numerous challenges, primarily stemming from difficulties in data access. Moreover, the specific constraints imposed by IoT devices further complicate the task of safeguarding the network against external threats and analyzing these threats effectively. In this current study, a range of existing methodologies has been explored to enhance the efficiency of intrusion detection systems, despite facing certain limitations and resource constraints. The principal objective of this research paper is to investigate the efficacy of existing intrusion detection systems integrated with genetic algorithm decision-making and coding techniques. By incorporating these techniques, the aim is to bolster the performance of intrusion detection systems and fortify them against external intrusion attempts.