Digital Terrestrial Tracking: The Future of Surveillance

ABSTRACT In this paper, the terms Digital Terrestrial Tracking (DTT) and Digital Terrestrial Footprint (DTF) are introduced. The DTF defines the uniquely identifiable signature of wireless signals emitted by a device or collection of devices that an individual carries on their person in the physical world. These signals can reveal a device's history at a location and point in time, and potentially disclose details about the owner. Interrogation or interaction with the device may reveal further details. The DTF positions itself between an individual's physical world footprint (their unique personal attributes), and their online footprint (defined by their unique online persona). Physical world tracking would involve following a person based on what they look or sound like; online tracking would involve tracking a person online activity based on their unique online signature (cookies, IP addresses, social media accounts); and digital terrestrial tracking involves tracking a person in the real world based on a unique signature emitted by devices on their person. The goal of the research conducted and discussed in this paper was to build a mass data collection and correlation framework based on information leaked from the wireless devices that people carry. The framework should be able to identify, track, and profile people by passively collected wireless information from devices, and collect information that is more verbose by optionally interrogating devices. The result is a tool, named Snoopy, written in Python, capable of operating in a distributed manner, in harsh environments on affordable off the shelf (OTS) hardware. Snoopy is able to draw specific and high level conclusions about individuals based on their digital wireless signals. The framework has been extensively tested in busy public areas (such as conferences, airports, hotels, etc.) and validated our hypothesis that such tracking was possible. Analysis performed against the collected data revealed interesting insights and trends, which will be discussed in the results section of this paper