Innovative Engineering with AI Applications

8A Study of WSN Privacy Through AI Technique

Piyush Raja

Department of CSE, COER University, Roorkee, India

Abstract

Wireless sensor network (WSN) collects data then interpret the informations about the environment or the object they are sensing. Owing to the energy and the bandwidth limit, those sensor usually has reduced communication capability. WSN keep track of changing conditions in real time. External variables or the device designers themselves are to blame for this complex behaviour. Sensor networks often use deep learning methods to respond to certain situations, avoiding the need for wasteful overhaul. Machine learning also inspires plenty of realistic strategies for maximising resource use and extending the network’s lifetime. We included a comparison guide in this paper to assist WSN designers in designing appropriate machine learning (ML) strategies for their unique implementation problems.

WSN (Wireless Sensor Network) are gaining popularity among researchers. One of the most important problems is to preserve their privacy. This region has received a significant amount of attention in recent years. Surveys and literature studies have also been conducted to provide a comprehensive overview of the various techniques. However, no previous research has focused on privacy models, or the set of assumptions utilised to construct the method. This work, in particular, focuses on this topic by reviewing 41 studies over the previous five years. We call attention to the ...