Assessing the Completeness of Passive Wi-Fi Traffic Capture
Mohammad Imran Syed, Anne Fladenmuller, Marcelo Dias de Amorim · 2022 International Wireless Communications and Mobile Computing (IWCMC) · 2022
The passive capture of Wi-Fi traces using sniffers is a cost-efficient and disturbance-free technique to assess the wireless activity of a target area. However, because of the inherent characteristics of the wireless medium, a sniffer is likely to miss Wi-Fi packets leading to incomplete traces. In this paper, we formulate the notion of relative completeness and investigate it experimentally. We consider anonymized Wi-Fi traces from 10 co-located sniffers in residential and office areas (different intensities of Wi-Fi traffic). We observe that individual sniffers lead to low completeness. Consequently, it is necessary to increase redundancy by packing several sniffers together (which we call a super-sniffer) to gather more complete traces. We observe that the results do not depend on the hardware but rather on the environment and that the results improve by increasing the size of the super-sniffer irrespective of the scenario.