Wireless Fidelity (Wi-Fi) Traffic Analysis: A Systematic Review

Abstract

In the era of pervasive connectivity, Wireless Fidelity networks have become essential to modern communication systems, facilitating seamless wireless internet access and data transmission across miscellaneous devices. As the adoption of Wireless Fidelity technology continues, the complexity of monitoring and optimizing these networks also increases. This systematic review aims to enhance the existing knowledge on Wireless Fidelity traffic analysis tools by conducting a rigorous assessment of current tools, their functionalities, and areas of expertise. The study adopts the pre-recording systematic reviews and meta-analysis method and a total of thirty-three articles were carefully extracted and analysed using the chosen search technique. These articles were classified into two main categories: machine learning techniques and other techniques. The outcomes of the review can be divided into distinct parts. Firstly, between 2018 and 2022, there were no studies conducted in Malaysia regarding Wireless Fidelity traffic analysis tools. Secondly, machine learning techniques were found to be particularly effective in extracting valuable insights related to user preferences, content consumption habits, and prevailing service usage trends. As a result, the future work should focus on proposing a new model for an intelligent Wi-Fi traffic analysis tool based on machine learning techniques, to be implemented and validated in real environments.