Signals from the crowd

Abstract

The ever increasing ubiquitousness of WiFi access points, coupled with the diffusion of smartphones, suggest that Internet every time and everywhere will soon (if not already has) become a reality. Even in presence of 3G connectivity, our devices are built to switch automatically to WiFi networks so to improve user experience. Most of the times, this is achieved by recurrently broadcasting automatic connectivity requests (known as Probe Requests) to known access points (APs), like, e.g., "Home WiFi", "Campus WiFi", and so on. In a large gathering of people, the number of these probes can be very high. This scenario rises a natural question: "Can significant information on the social structure of a large crowd and on its socioeconomic status be inferred by looking at smartphone probes?".In this work we give a positive answer to this question. We organized a 3-months long campaign, through which we collected around 11M probes sent by more than 160K different devices. During the campaign we targeted national and international events that attracted large crowds as well as other gatherings of people. Then, we present a simple and automatic methodology to build the underlying social graph of the smartphone users, starting from their probes. We do so for each of our target events, and find that they all feature social-network properties. In addition, we show that, by looking at the probes in an event, we can learn important sociological aspects of its participants-language, vendor adoption, and so on.

Decomposition of MAC address structure for granular device inference

“…• Validation of our model fingerprinting against a thirdparty dataset with > 80% accuracy, and a practical application of locally assigned MAC address derandomization introduced in [6,27]. Additionally, we achieve high precision and recall validating against a known set of 279 devices.…”

“…To evaluate our technique, we validate against a thirdparty corpus of publicly available probe requests in CRAW-DAD from Sapienza [6]. This dataset consists of approximately 11M probes requests on behalf of 160,000 unique de- vices.…”

Building up knowledge through passive WiFi probes

“…After performing a collection campaign of probe requests lasted about 3 months and targeting events of International, National, and Citywide relevance, the authors of [24] focus on discovering socialrelated phenomena like: the distribution of languages of the people participating in the events, the vendors of the devices they use, and, based on the cost of the different brands, give insights on the wealth of the population.…”

Crowd Mobility Analysis using WiFi Sniffers

“…They present an approach for detecting wifi probes and estimating the spatio-temporal trajectories of smart phones. In [5], by only looking at WiFi probes, Barbera et al was able to infer significant information on the social structure of a large crowd and its socioeconomic status. In [6], Chon et al use smart phones as sniffers to demystify the potential and the threat that exist in sniffing wifi probes.…”