How To Mitigate And Defend Against DDoS Attacks In IoT Devices

TL;DR

This paper analyzes DDoS threats in IoT networks and proposes layered mitigation strategies including IPv6 ULA, edge computing, SDN, honeypots, and machine learning-based intrusion detection to enhance security.

Contribution

It introduces a comprehensive framework combining multiple mitigation techniques specifically designed for IoT environments to counteract DDoS attacks.

Findings

Layered mitigation strategies effectively reduce DDoS impact on IoT devices.

Machine learning-based intrusion detection improves attack detection accuracy.

Implementation of IPv6 ULA and SDN enhances network resilience.

Abstract

Distributed Denial of Service (DDoS) attacks have become increasingly prevalent and dangerous in the context of Internet of Things (IoT) networks, primarily due to the low-security configurations of many connected devices. This paper analyzes the nature and impact of DDoS attacks such as those launched by the Mirai botnet, and proposes layered mitigation strategies tailored to IoT environments. Key solutions explored include IPv6 Unique Local Addresses (ULA), edge computing, software-defined networking (SDN), honeypot deception, and machine learning-based intrusion detection systems. The paper aims to help engineers and researchers understand and implement practical countermeasures to protect IoT infrastructures.