We investigate the ability of an attacker to passively use an otherwise secure wireless network to detect moving people through walls. We call this attack on privacy of people a "monitoring radio windows" (MRW) attack. We design and implement the MRW attack methodology to reliably detect when a person crosses the link lines between the legitimate transmitters and the attack receivers, by using physical layer measurements. We also develop a method to estimate the direction of movement of a person from the sequence of link lines crossed during a short time interval. Additionally, we describe how an attacker may estimate any artificial changes in transmit power (used as a countermeasure), compensate for these power changes using measurements from sufficient number of links, and still detect line crossings. We implement our methodology on WiFi and ZigBee nodes and experimentally evaluate the MRW attack by passively monitoring human movements through external walls in two real-world settings. We find that achieve close to 100% accuracy in detecting line crossings and determining direction of motion, even through reinforced concrete walls.
New techniques in cross-layer wireless networks are building demand for ubiquitous channel sounding, that is, the capability to measure channel impulse response (CIR) with any standard wireless network and node. Towards that goal, we present a software-defined IEEE 802.11b receiver and CIR measurement system with little additional computational complexity compared to 802.11b reception alone. The system implementation, using the universal software radio peripheral (USRP) and GNU Radio, is described and compared to previous work. We validate the CIR measurement system and present the results of a measurement campaign which measures millions of CIRs between WiFi access points and a mobile receiver in urban and suburban areas.
The ability for special operations forces (SOF) to rapidly deploy a through-building tracking system upon arrival at a tactical operation, e.g., a hostage scenario, and thereby estimate the approximate locations of the people within the building has the potential to lower the risk of the operation and save lives. We study the feasibility of a rapidly deployed radio frequency (RF)-based tomographic imaging (RTI) system for use in tactical operations by Special Weapons and Tactics (SWAT) and other SOF, in which several low-power radio devices are placed around a building and used to image and track the motion of humans inside the building. Specifically, we identify and study the constraints of this application, such as the need for the sensor network to self-localize and self-calibrate with minimal input from the SOF. We implement and test, in a wide variety of experimental deployments, a real-time RTI tracking system which adheres to these constraints and provides valuable situational intelligence. We work in concert with local law enforcement and SWAT in order to obtain valuable feedback from end users. We show that our system is capable of providing useful tracking information (average errors of less than two meters) even when the self-localization results are inaccurate (up to three meters average error).
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