Protecting the IoT Devices from DDoS Attack Using Blockchain-Based Multi-code-Driven Trust Mechanism

The Internet of things (IoT) offers a promising platform for developing mission-critical programs. However, these programs often depend on a centralised storage architecture, which poses significant challenges such as security, privacy, and a single point of failure. Recently, blockchain technology has emerged as a key component in IoT application development. Blockchain can address issues related to data privacy, security, and third-party dependence in IoT applications. Both individuals and communities can benefit from integrating blockchain with IoT. Nonetheless, a DDoS attack on a mining pool in 2017 exposed significant vulnerabilities in blockchain-enabled IoT systems. Additionally, the data generated by these programs is vast. Machine learning (ML) is an effective analytical tool that facilitates fully autonomous analysis and decision-making with large datasets. This research proposes a novel distributed intrusion detection system (IDS) utilising fog computing to detect DDoS attacks on mining pools in blockchain-enabled IoT networks, addressing the aforementioned challenges. It introduces an energy-efficient, decentralised, blockchain-based multi-mobile code-driven method for detecting internal threats in sensor node-powered IoT. The results indicate that the proposed approach outperforms existing alternatives.