Using Naive Bayes Algorithm in the Internet of Things secure Drone-Cyber

Recent developments in drone technologies enable new options and uses, particularly in miniature drones, which may be used in a wide range of settings. But these innovations also introduce new safety, flexibility, and uniformity difficulties. The commercial and military sectors may both benefit from small drones. There are problems with the design of the tiny drones and the way that security and safety are defined for them. Drone technology may now be used in previously unimaginable contexts, but the proliferation of IoT also introduces new risks. The data security and privacy risks the tiny flying intelligent gadgets pose are significant. Small drone design has yet to reach a point of maturity where it can meet the sector’s demands. Data conversions, privacy safeguards, and security measures are all necessary additions to the fundamental design problems. Security and flexibility issues with these modern drones may be mitigated by learning more about infiltration and interception in the Internet of Drones (IoD) space. In this study, presents the development of an Internet of Things-enabled drone using a machine-learning technique. An intelligent cyber security system may identify malicious Blockchain transactions using this strategy.