Review on Intrusive Detection to Secure Social Internet of Things in Edge Computing

Abstract

Abstract: This review paper presents an analysis of the latest developments in Intrusion Detection Systems (IDSs) for securing the Social Internet of Things (SIoT). The authors focus on the limitations of conventional IDSs and underscore the importance of leveraging advanced techniques, particularly deep learning, for efficient and effective intrusion detection in SIoT. The article evaluates various recent research studies that have utilized deep learning models for intrusion detection in SIoT. It discusses the types of deep learning models employed and offers valuable insights into the current state-of-the-art in IDSs for securing SIoT. The review concludes by highlighting the potential of deep learning techniques in achieving accurate and effective intrusion detection in SIoT networks.