Conference PaperRule-Based Hybrid Adaptive Encryption Model for Autonomous Flight to Secure UAS Data Streams in Real-TimeAnaroua, Fadjimata I; Liu, Yongxin; Liu, HongGiven the increasing reliance on UAS in sensitive applications, ensuring the confidentiality, integrity, and availability of their data streams is paramount. Traditional encryption methods often fail to balance performance and security under real-time constraints. This paper addresses this gap by proposing a hybrid adaptive encryption framework that integrates rule-based (RL) logic and machine learning (ML) to dynamically adjust encryption protocols based on data sensitivity, bandwidth, and CPU load. The experimental results demonstrate improved responsiveness and security under varied conditions using real-time simulations. The effectiveness of the system is benchmarked through execution time analysis, classification accuracy, and adaptive decision precision, highlighting its potential for secure and efficient UAS communications.IEEE2025-05-1910636646333 to 340979-8-3503-9292-0https://doi.org/10.1109/ICSC65596.2025.111405632142514adaptive encryption, data streams, cryptography, threat intelligence, autonomous systems, system resources, environmental factorsTampa, FL, USANational Science Foundation