An anonymous reader quotes a report from The Stack: Researchers at Stanford and Princeton have succeeded in identifying 70% of web users by comparing their web-browsing history to publicly available information on social networks. The study "De-anonymizing Web Browsing Data with Social Networks" [PDF] found that it was possible to reattach identities to 374 sets of apparently anonymous browsing histories simply by following the connections between links shared on Twitter feeds and the likelihood that a user would favor personal recommendations over abstract web browsing. The test subjects were provided with a Chrome extension that extracted their browsing history; the researchers then used Twitter's proprietary URL-shortening protocol to identify t.co links. 81% of the top 15 results of each enquiry run through the de-anonymization program contained the correct re-identified user -- and 72% of the results identified the user in first place. Ultimately the trail only leads as far as a Twitter user ID, and if a user is pseudonymous, further action would need to be taken to affirm their real identity. Using https connections and VPN services can limit exposure to such re-identification attempts, though the first method does not mask the base URL of the site being connected to, and the second does not prevent the tracking cookies and other tracking methods which can provide a continuous browsing history. Additionally UTM codes in URLs offer the possibility of re-identification even where encryption is present. Further reading available via The Atlantic.