Though most users feel anonymous when browsing the Web, their browsers constantly turn over unique information such as a list of installed plugins, screen resolution, and the user agent string. Taken together, such bits of information can uniquely identify many users even without cookies.
But this is now old tech; behavioral analytics firms have already moved on. Cookies, browser signatures, and IP addresses can all help identify particular machines and particular browsers—but how can you tell which human actually sits behind the terminal at a given moment? One way is by measuring the "cadence" of their typing.
Scout Analytics has done just that in order to help its 40 paid content clients detect and stop those "sharing" their accounts without permission. 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.
Cookies, browsers, and biometrics
That's where a company like Scout comes in. I spoke with Matt Shanahan, VP of Strategy for the company, about a research project that Scout just concluded that tried to figure out exactly when more than one person was using a single named account.
At first, Scout of course tried using cookies to track this information, but this produced terrible data; it suggested that six or seven different devices were being used to access each account, a number that seemed far too high to be plausible. So Scout then added browser data, of the kind highlighted by the EFF's recent Panopticlick project, to prevent problems like cleared cookies. When applied to a data set of 20 million actual logins to paid content sites, this refined technique identified nearly 600,000 unique devices being used for access.