Imagine that you sell access to an expensive database, so expensive that users are routinely tempted to share their “named accounts” with others in the office rather than pay for additional licenses. You would probably want to “encourage” these users to pay up or stop sharing the account, but it’s difficult to know which logins are legitimate and which are not.

Scout used some Javascript timing features to watch how users type when they enter their login credentials for various services. Shanahan says that his algorithms need a minimum of 5 attempts at entering a phrase of at least 12 characters in order to generate a typing “cadence.” By watching repeated logins, Scout could soon categorize these cadences into a digital pattern, then assign each pattern a serial number.

“As you’re typing, you have a cadence and rhythm,” Shanahan says, a rhythm that includes how long one holds down various keys and how long it takes to move between keys. Applying the technology to its data set of 20 million logins, Scout pulled out 175,000 unique patterns—thereby identifying 175,000 distinct users, even when they used the same login credentials on the same machine.

See the full post here.