Evaluating deep learning variants for cyber-attacks detection and multi-class classification in IoT networks.

ABSTRACT: The Internet of Things (IoT), considered an intriguing technology with substantial potential for tackling many societal concerns, has been developing into a significant component of the future. The foundation of IoT is the capacity to manipulate and track material objects over the Internet. The IoT network infrastructure is more vulnerable to attackers/hackers as additional features are accessible online. The complexity of cyberattacks has grown to pose a bigger threat to public and private sector organizations. They undermine Internet businesses, tarnish company branding, and restrict access to data and amenities. Enterprises and academics are contemplating using machine learning (ML) and deep learning (DL) for cyberattack avoidance because ML and DL show immense potential in several doma

SUBMITTER: Abbas S 

PROVIDER: S-EPMC10803060 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature