Browser Fingerprinting Tech Works Across Different Browsers for the First Time

Web browsing just got a little less anonymous: New browser fingerprinting software correctly identifies 99% of online users even if they switch browsers

3 min read
A photo illustration shows the icons that represent several web browsers, incluing Chrome and Firefox, in a row
Photo-illustration: iStockphoto

Browsing the Web just got a little less anonymous. The software that lets websites identify you by certain characteristics of your computer and software was usually thwarted if you switched browsers. But now computer scientists have developed new browser fingerprinting software that identifies users across Web browsers with a degree of accuracy that beats the most sophisticated single-browser techniques used today.

The new method, created by Yinzhi Cao, a computer science professor at Lehigh University, in Pennsylvania, accurately identifies 99.24 percent of users across browsers, compared to 90.84 percent of users identified by AmIUnique, the most advanced single-browser technique.

Browser fingerprinting is an online tracking technique commonly used to authenticate users for retail and banking sites and to identify them for targeted advertising. By combing through information available from JavaScript and the Flash plugin, it’s possible for third parties to create a “fingerprint” for any online user.

That fingerprint includes information about users’ browsers and screen settings—such as screen resolution or which fonts they’ve installed—which can then be used to distinguish them from someone else as they peruse the Web.

In the past, though, these techniques worked only if people continued to use the same browser—once they switched, say, to Firefox from Safari, the fingerprint was no longer very useful. Now, Cao’s method allows third parties to reliably track users across browsers by incorporating several new features that reveal information about their devices and operating systems.

Cao, along with his colleagues at Lehigh and Washington University, in St. Louis, began creating their tech by first examining the 17 features included in AmIUnique, the popular single-browser fingerprinting system, to see which ones might also work across browsers.

For example, one feature that AmIUnique relies on is screen resolution. Cao found that screen resolution can actually change for users if they adjust their zoom levels, so it’s not a very reliable feature for any kind of fingerprinting. As an alternative, he used a screen’s ratio of width to height because that ratio remains consistent even when someone zooms in.

Cao borrowed or adapted four such features from AmIUnique for his own cross-browser technique, and he also came up with several new features that revealed details about users’ hardware or operating systems, which remain consistent no matter which browser they open.

The new features he developed include an examination of a user’s audio stack, graphics card, and CPU. Overall, he relied on a suite of 29 features to create cross-browser fingerprints.

To extract that information from someone’s computer, Cao wrote scripting languages that force a user’s system to perform 36 tasks. The results from these tasks include information about the system, such as the sample rate and channel count in the audio stack. It takes less than a minute for the script to complete all 36 tasks.

To test the accuracy of his 29-point method, Cao recruited 1,903 helpers from Amazon Mechanical Turks and Microworkers. He asked them to visit a website from multiple browsers and found that the method worked across many popular browsers, including Google Chrome, Internet Explorer, Safari, Firefox, Microsoft Edge Browser, and Opera, as well as a few obscure ones, such as Maxthon and Coconut.

Cao tried removing several of the 29 features, and their related tasks, to see if he could use even fewer to achieve the same degree of accuracy, but he found that doing so lowered the accuracy slightly each time. “One is not a standout,” he says.

The only browser that his method didn’t work on was Tor. Earlier this month, Cao published the open source code for his technique so that anyone could use it. His next step? To work on more ways that users can avoid being fingerprinted across browsers, should they wish to opt out.

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Metamaterials Could Solve One of 6G’s Big Problems

There’s plenty of bandwidth available if we use reconfigurable intelligent surfaces

12 min read
An illustration depicting cellphone users at street level in a city, with wireless signals reaching them via reflecting surfaces.

Ground level in a typical urban canyon, shielded by tall buildings, will be inaccessible to some 6G frequencies. Deft placement of reconfigurable intelligent surfaces [yellow] will enable the signals to pervade these areas.

Chris Philpot

For all the tumultuous revolution in wireless technology over the past several decades, there have been a couple of constants. One is the overcrowding of radio bands, and the other is the move to escape that congestion by exploiting higher and higher frequencies. And today, as engineers roll out 5G and plan for 6G wireless, they find themselves at a crossroads: After years of designing superefficient transmitters and receivers, and of compensating for the signal losses at the end points of a radio channel, they’re beginning to realize that they are approaching the practical limits of transmitter and receiver efficiency. From now on, to get high performance as we go to higher frequencies, we will need to engineer the wireless channel itself. But how can we possibly engineer and control a wireless environment, which is determined by a host of factors, many of them random and therefore unpredictable?

Perhaps the most promising solution, right now, is to use reconfigurable intelligent surfaces. These are planar structures typically ranging in size from about 100 square centimeters to about 5 square meters or more, depending on the frequency and other factors. These surfaces use advanced substances called metamaterials to reflect and refract electromagnetic waves. Thin two-dimensional metamaterials, known as metasurfaces, can be designed to sense the local electromagnetic environment and tune the wave’s key properties, such as its amplitude, phase, and polarization, as the wave is reflected or refracted by the surface. So as the waves fall on such a surface, it can alter the incident waves’ direction so as to strengthen the channel. In fact, these metasurfaces can be programmed to make these changes dynamically, reconfiguring the signal in real time in response to changes in the wireless channel. Think of reconfigurable intelligent surfaces as the next evolution of the repeater concept.

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