Security Enhancements in Wireless Sensor Networks: Issues, Strategies, and Prospective Directions – A Systematic Review

Abstract

This systematic review draws together findings from over 90 studies spanning 1999 to 2025 to explore security enhancements in Wireless Sensor Networks (WSNs). It offers a thorough examination of security obstacles, appraises both conventional and novel countermeasures, and highlights key areas where research falls short. Following PRISMA guidelines and sourcing from repositories like IEEE Xplore, ACM Digital Library, ScienceDirect, Scopus, and Web of Science, we applied thematic analysis to reveal central patterns. Principal observations point to ongoing weaknesses tied to limited resources and vulnerable transmission paths, as well as shortcomings in trust mechanisms, encryption methods, and machine learning applications when it comes to expanding scale and conserving power. Technologies on the horizon, such as Blockchain, Post-Quantum Cryptography (PQC), and Software-Defined Networking (SDN), present strong opportunities but face obstacles in fitting seamlessly into WSNs. Setting this apart from earlier overviews, our work puts forward a blended framework that combines Federated Learning (FL) with streamlined PQC to tackle privacy concerns and quantum risks, underscoring overlooked potentials in combined systems. We note lasting deficiencies in expandable trust setups, power-saving real-time intrusion detection, workable PQC rollout, and strong privacy protections. The review calls for directed studies into Blockchain-FL combinations, power-sensitive procedures, and joint hardware-software designs to strengthen WSN security moving forward. These observations provide actionable advice for those building systems to create sturdy WSNs in essential IoT settings, including intelligent urban areas and medical care, against the backdrop of an IoT sector expected to top US$1.06 trillion by 2025.