Designing an adaptive modular management system for data security in Multi-UAV by using a pattern language approach - Gregorius Airlangga (Institute of Computer Science (IOCS), 2024)
In the rapidly evolving landscape of Unmanned Aerial Vehicle (UAV) technology, the dynamic and unpredictable nature of operational environments presents substantial challenges for data security systems. This research introduces a novel software pattern design tailored for enhancing data security in online UAV operations within such environments. Inspired by the principles of the Pattern Language of Program Community (PLOP), this study proposes a comprehensive design pattern focused on modularity, adaptability, and scalability. The proposed design intricately combines various software patterns, forming a unified framework that addresses key aspects of UAV data security operations, including real-time adaptability, environmental responsiveness, and efficient resource management. The architecture of this framework integrates behavioral, structural, and creational patterns, meticulously selected to bolster the UAVs’ decision-making capabilities, data handling, and dynamic adaptation in response to changing environmental and operational conditions. Theoretical analysis and conceptual evaluations underpin this research, favoring a detailed theoretical exploration over empirical experimentation. This approach allows for an in-depth examination of the design’s potential and applicability in the context of UAV data security. The research contributes to the UAV field by offering a structured and standardized methodology, laying a robust theoretical foundation for future empirical studies and practical implementations. The goal is to significantly enhance the security, efficiency, and safety of UAV operations in dynamic and challenging environments, setting a new benchmark for data security solutions in the realm of UAV technology.