Enhancing AI-Driven DDoS Mitigation in SAGIN Networks via Blockchain Integration

Abstract

Satellite communication (SATCOM) networks are essential in delivering long-range and high-capacity data transmission on a global basis. With emerging satellite-ground-air integrated networks (SAGIN) responding to growing demands for communication and low-latency connections, their unique, dynamic infrastructure raises novel issues in security. Traditional centralized defenses are increasingly ineffective against advanced attacks such as distributed denial-of-service (DDoS). This research advocates an integrated solution that combines blockchain infrastructure with deep learning approaches to address these security challenges. The model was simulated in an NS-3 environment, and normal and attack traffic were generated to train a hybrid CNN-LSTM-based anomaly detection model. Distinct types of threats were recorded on a private Ethereum-based blockchain using smart contracts, enabling decentralized blacklist control and automated response behaviors. With decentralized control of threats, detection efficiency is enhanced by application of AI-driven analysis, and trust is ensured by virtue of immutable logging. The test results hold promise for this solution in delivering scalable, robust, and autonomous security for modern SATCOM networks.