IoT-Empowered Drones: Smart Cyber security Framework with Machine Learning Perspective

Innovations in drone technology, especially for smaller drones, have sparked new developments and opportunities across various fields. The IoT enables drones to provide services like GPS navigation between different locations. However, design defects in drone networks pose privacy and security threats. Building a secure network is essential to achieving the required performance. This research examines new privacy and security issues impact on the NoD (network of drones).The findings of this study highlight the need for a secure drone network to avoid eavesdropping and infiltration. For optimal efficiency, classify data instances using a mixture of the ML techniques of logistic regression (LR) and random forest. The suggested method reduces the risk of cyber-attacks by shoring up the foundation of a NoD with cutting-edge artificial intelligence-inspired approaches. The proposed method is validated by applying it to a complex data set; the results show improvements in terms of speed (35.67 seconds), accuracy (99.69 per cent), recall (99.70 per cent), F-measure (99.98 per cent), reliability (95.80 per cent), and stability (1.84).