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Knowledge of Wi-Fi networks helps to guide future engineering and spectrumpolicy decisions. However, due to its unlicensed nature, the deployment ofWi-Fi Access Points is undocumented meaning researchers are left makingeducated guesses as to the prevalence of these assets through remotelycollected or passively sensed measurements. One commonly used method isreferred to as `wardriving` essentially where a vehicle is used to collectgeospatial statistical data on wireless networks to inform mobile computing andnetworking security research. Surprisingly, there has been very littleexamination of the statistical issues with wardriving data, despite the vastnumber of analyses being published in the literature using this approach. Inthis paper, a sample of publicly collected wardriving data is compared to apredictive model for Wi-Fi Access Points. The results demonstrate severalstatistical issues which future wardriving studies must account for, includingselection bias, sample representativeness and the modifiable areal unitproblem.

Wi-Fi Wardriving Studies Must Account for Important Statistical Issues