Tag Archives: personal data

Your Phone Is Listening: smart-phones as sniffers

U. S. government agencies from the military to law enforcement have been buying up mobile-phone data from the private sector to use in gathering intelligence, monitoring adversaries and apprehending criminals. Now, the U.S. Air Force is experimenting with the next step.

The Air Force Research Laboratory is testing a commercial software platform that taps mobile phones as a window onto usage of hundreds of millions of computers, routers, fitness trackers, modern automobiles and other networked devices, known collectively as the “Internet of Things.” SignalFrame, a Washington, D.C.-based wireless technology company, has developed the capability to tap software embedded on as many as five million cellphones to determine the real-world location and identity of more than half a billion peripheral devices. The company has been telling the military its product could contribute to digital intelligence efforts that weave classified and unclassified data using machine learning and artificial intelligence.

The Air Force’s research arm bought the pitch, and has awarded a $50,000 grant to SignalFrame as part of a research and development program to explore whether the data has potential military applications, according to documents reviewed by The Wall Street Journal. Under the program, the Air Force could provide additional funds should the technology prove useful.

SignalFrame has largely operated in the commercial space, but the documents reviewed by the Journal show the company has also been gunning for government business. A major investor is Razor’s Edge, a national-security-focused venture-capital firm. SignalFrame hired a former military officer to drum up business and featured its products at military exhibitions, including a “pitch day” sponsored by a technology incubator affiliated with U.S. Special Operations command in Tampa, Fla.

SignalFrame’s product can turn civilian smartphones into listening devices—also known as sniffers—that detect wireless signals from any device that happens to be nearby. The company, in its marketing materials, claims to be able to distinguish a Fitbit from a Tesla from a home-security device, recording when and where those devices appear in the physical world. Using the SignalFrame technology, “one device can walk into a bar and see all other devices in that place,” said one person who heard a pitch for the SignalFrame product at a marketing industry event…

“The capturing and tracking of unique identifiers related to mobile devices, wearables, connected cars—basically anything that has a Bluetooth radio in it—is one of the most significant emerging privacy issues,” said Alan Butler, the interim executive director and general counsel of the Electronic Privacy Information Center, a group that advocates for stronger privacy protections. “Increasingly these radios are embedded in many, many things we wear, use and buy,” Mr. Butler said, saying that consumers remain unaware that those devices are constantly broadcasting a fixed and unique identifier to any device in range.

Byron Tau,  Military Tests New Way of Tracking, WSJ, Nov. 28, 2020

Behavior Mining

Understanding and assessing the readiness of the warfighter is complex, intrusive, done relatively infrequently, and relies heavily on self-reporting. Readiness is determined through medical intervention with the help of advanced equipment, such as electrocardiographs (EKGs) and otherspecialized medical devices that are too expensive and cumbersome to employ continuously without supervision in non-controlled environments. On the other hand, currently 92% of adults in the United States own a cell phone, which could be used as the basis for continuous, passive health and readiness assessment.  The WASH program will use data collected from cellphone sensors to enable novel algorithms that conduct passive, continuous, real-time assessment of the warfighter.

DARPA’s WASH [Warfighter Analytics using Smartphones for Health] will extract physiological signals, which may be weak and noisy, that are embedded in the data obtained through existing mobile device sensors (e.g., accelerometer, screen, microphone). Such extraction and analysis, done on a continuous basis, will be used to determine current health status and identify latent or developing health disorders. WASH will develop algorithms and techniques for identifying both known indicators of physiological problems (such as disease, illness, and/or injury) and deviations from the warfighter’s micro-behaviors that could indicate such problems.

Excerpt from Warfighter Analytics using Smartphones for Health (WASH)
Solicitation Number: DARPA-SN-17-4, May, 2, 2018

See also Modeling and discovering human behavior from smartphone sensing life-log data for identification purpose