IoT Routing Reimagined: Dynamic Phantom Routing with ACO for Efficient Source Location Privacy

Several low-power sensors make up the Internet of Things (IoT), which collects a variety of useful and personally relevant data. We pay particular attention to a few privacy concerns with device location data. An evolutionary and built-in method of exploring the search space while safeguarding the location privacy of IoT nodes is provided by ant colony optimization. In this paper, we focus on protecting the node's position with appropriate modifications to IoT routing. First we introduced dynamic phantom node selection and then created multiple paths and chose the optimal path with ant colony optimization (ACO) technique. With extensive simulation in NS2, we proved that our approach achieves better results compared to existing techniques in terms of energy, safety period, and overall network lifetime.