Tag Archives: behavior mining

Your Typing Discloses Who You Are: Behavioral Biometrics

Behavioural biometrics make it possible to identify an individual’s “unique motion fingerprint”,… With the right software, data from a phone’s sensors can reveal details as personal as which part of someone’s foot strikes the pavement first, and how hard; the length of a walker’s stride; the number of strides per minute; and the swing and spring in the walker’s hips and step. It can also work out whether the phone in question is in a handbag, a pocket or held in a hand.

Using these variables, Unifyid, a private company, sorts gaits into about 50,000 distinct types. When coupled with information about a user’s finger pressure and speed on the touchscreen, as well as a device’s regular places of use—as revealed by its gps unit—that user’s identity can be pretty well determined, ction….Behavioural biometrics can, moreover, go beyond verifying a user’s identity. It can also detect circumstances in which it is likely that a fraud is being committed. On a device with a keyboard, for instance, a warning sign is when the typing takes on a staccato style, with a longer-than-usual finger “flight time” between keystrokes. This, according to Aleksander Kijek, head of product at Nethone, a firm in Warsaw that works out behavioural biometrics for companies that sell things online, is an indication that the device has been hijacked and is under the remote control of a computer program rather than a human typist…

Used wisely, behavioural biometrics could be a boon…Used unwisely, however, the system could become yet another electronic spy on people’s privacy, permitting complete strangers to monitor your every action, from the moment you reach for your phone in the morning, to when you fling it on the floor at night.

Excerpts from Behavioural biometrics: Online identification is getting more and more intrusive, Economist, May 23, 2019

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