Securing Wireless Sensor Networks Using Machine Learning and Blockchain: A Review

Abstract

As an Internet of Things (IoT) technological key enabler, Wireless Sensor Networks (WSNs) are prone to different kinds of cyberattacks. WSNs have unique characteristics, and have several limitations which complicate the design of effective attack prevention and detection techniques. This paper aims to provide a comprehensive understanding of the fundamental principles underlying cybersecurity in WSNs. In addition to current and envisioned solutions that have been studied in detail, this review primarily focuses on state-of-the-art Machine Learning (ML) and Blockchain (BC) security techniques by studying and analyzing 171 up-to-date publications highlighting security aspect in WSNs. Then, the paper discusses integrating BC and ML towards developing a lightweight security framework that consists of two lines of defence, i.e, cyberattack detection and cyberattack prevention in WSNs, emphasizing the relevant design insights and challenges. The paper concludes by presenting a proposed integrated BC and ML solution highlighting potential BC and ML algorithms underpinning a less computationally demanding solution.

Special Issue on Security and Privacy in Blockchains and the IoT Volume II

“…The first review is focused on how a network can be secured using blockchain technology. Ismail et al [16] specifically consider wireless sensor networks (WSNs), which are the enabler technology for the IoT. Since the devices deployed in these networks are usually rather rudimentary, they often lack sufficient security measures, which is why they are prone to cyberattacks.…”

A Review of Blockchain Technology in Knowledge-Defined Networking, Its Application, Benefits, and Challenges

“…The review paper in [68] presents the fusion of blockchain and ML for 5G and beyond IoT networks. Similarly, review papers [69][70][71] review the blockchain and machine learning integrated frameworks for wireless sensor networks and smart grids, with an emphasis on security and privacy. Different from the previously mentioned surveys, our survey involves reviewing the application of blockchain technology in knowledge-defined networking.…”

“…Therefore, compared to surveys on blockchain in generic SDN [65][66][67], our survey is for a special futuristic case of SDN, where knowledge is generated using machine learning/artificial intelligence/fuzzy logic/meta-heuristic techniques for blockchain applications. Moreover, compared to previous surveys [68][69][70][71], our survey has a broad perspective, having generic knowledge-driven (not only limited to machine learning, but also addressing other heuristic knowledge-generation techniques such as optimization, meta-heuristics, fuzzy logic, etc.) network applications without being bound to the security and privacy applications of a special network category of knowledge-based networks.…”