AI-Driven Secure UAV Communication Framework for Document Delivery in Sensitive Areas with 5G

With the advent of technology, the transfer of sensitive information has become more prone to misuse, especially through unsecured platforms like social media. To address this challenge, UAV communication, particularly drones, has emerged as an alternative for document delivery in highly sensitive areas. But these devices can also get vulnerable to attacks which can cause a serious issue when the information is sensitive. Therefore, we propose a UAV-based secure document delivery framework that leverages AI models to detect potential attacks on the UAVs. The system ensures security throughout the document transfer process by evaluating various drone parameters. We employ the Decision Tree Classifier, which uses entropy to classify the potential threats. The result of the classification is used to guide the decision-making process for a secure delivery process. We further compare the various models based on metrics like accuracy, precision, recall, and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{F - 1}$</tex> score, demonstrating the effectiveness of our framework, which enhances the security of UAV-based communication systems.