SHoM: A Mental-Synthesis Trust Management Model for Mitigating Botnet-Driven DDoS Attacks in the Internet of Things

TL;DR

This paper proposes SHoM, a trust management model designed to enhance IoT security by mitigating botnet-driven DDoS attacks, considering comprehensive trust factors for improved reliability.

Contribution

The paper introduces a novel trust management framework specifically tailored to defend IoT networks against DDoS attacks caused by botnets, incorporating extensive security factor analysis.

Findings

The model effectively detects and mitigates DDoS attacks in IoT environments.

Trust management improves IoT device security and resilience.

The approach outperforms existing security models in robustness.

Abstract

The advantages of IoT in strengthening commercial, industrial, and social ecosystems have led to its widespread expansion. Nevertheless, because endpoint devices have limited computation, storage, and communication capabilities, the IoT infrastructure is vulnerable to several cyber threats. As a result, DDoS attacks pose a severe risk to the security of IoT. By taking advantage of these weaknesses, attackers may quickly employ IoT devices as a component of botnets to execute DDoS attacks. The most critical development is how more armies of robots are being constructed from IoT devices. We offer a Model for dealing with DDOS attacks on botnets in the Internet of Things via trust management. In this Model, an attempt has been made to consider all aspects of security concerning trust factors to design a reliable and flexible model against DDoS attacks against the Internet of Things. In the initial studies, about 40-50 security models related to the subject have been studied by using review articles