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| Format: | Recurso digital |
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Zenodo
2025
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| Online Access: | https://doi.org/10.5281/zenodo.15811780 |
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Table of Contents:
- <p><strong><span>Purpose:</span></strong><span> As the world's reliance on satellite-based systems for communication, navigation, defence, and scientific research grows, cybersecurity for space systems has emerged as a key frontier. Satellites and their accompanying ground infrastructure are vulnerable to a growing number of cyber threats, including signal spoofing, jamming, unauthorized command injection, malware infiltration, and supply chain intrusion. These risks are exacerbated by space assets' lengthy operational lifetimes, physical inaccessibility, and rising interconnection. This study investigates the cybersecurity concerns specific to space systems, examines documented and possible attack vectors, and assesses current defence techniques such as encryption, intrusion detection systems, and secure communication protocols. In addition, we investigate the importance of predictive threat modelling and pattern analysis in proactively detecting new cyber hazards. Employing anomaly detection based on AI and machine learning. Additionally, we look into how crucial pattern analysis and predictive threat modelling are to proactively identifying emerging cyberthreats. Using machine learning and AI-based anomaly detection, predictive cybersecurity seeks to foresee possible attack vectors by evaluating telemetry data, communication patterns, and past attack signatures. Integrating predictive analytics enables automated reaction strategies, enhanced situational awareness, and early detection—all essential for safeguarding space systems in an ever-changing threat environment. This study combines cybersecurity, aeronautical engineering, and predictive analytics to present a holistic outlook on protecting satellite infrastructure from existing and future cyber threats.</span></p> <p><strong><span>Keywords:</span></strong><span> Cybersecurity; space systems security; satellite cybersecurity; predictive threat modelling; pattern analysis; machine learning; AI-driven anomaly detection; satellite communication; cyber-physical security; quantum key distribution; secure satellite control</span></p>