SAT-IOTA: A Cybersecurity Reinforcement Framework for Blockchain-Driven Space Satellites Utilizing Anomaly Prediction

Abstract

This paper introduces SAT-IOTA, a lightweight and AI-driven cybersecurity framework designed for blockchain-powered satellite infrastructures. Unlike traditional detection approaches, SAT-IOTA employs predictive anomaly analytics combined with a Sliding Window (SW) machine learning mechanism to proactively identify and mitigate security threats in space-air-ground integrated networks (SAGINs). The proposed framework integrates IOTA distributed ledger technology (DLT) for secure, decentralized telemetry data management, tokenized satellite components, and resilience against cyber-physical attacks. Through a custom-built testbed with Hornet nodes, we evaluate the frameworks performance under denial-of-service (DoS) scenarios, achieving 97% prediction accuracy and an F-measure of 80%. The results confirm that SAT-IOTA enhances space system security by combining blockchain-driven trust with AI-based anomaly prediction, offering a scalable and resource-efficient solution for next-generation satellite communications.