Improving Network Security using Tunicate Swarm Algorithm with Stacked Deep Learning Model on IoT Environment

摘要: The Internet of Things (IoT) represents important security vulnerabilities, increasing difficulties in cyberattacks. Attackers employ these vulnerabilities to establish distributed denial-of-service (DDoS) attacks, compromising availability and causing financial losses to digital platforms. Newly, numerous Machine Learning (ML) and Deep Learning (DL) approaches have been presented for the identification of botnet attacks in IoT networks. By analyzing the patterns of communication and behavior of IoT devices, DL algorithms will be differentiated between malicious and normal activity, therefore supporting the earlier detection and avoidance of botnet attacks. This is essential to protect the integrity and security of IoT systems that can be increasingly vulnerable to botnet-driven attacks because of their limited security measures and often large-scale applications. In this aspect, this study designs an innovative tunicate …