This is even though over 96% of third-party cookies are removed. This implementation effectively prevents all cookie tracking, and rarely breaks the user-experience on web pages. When this happens, the third party is temporarily whitelisted to allow cookies. To enable this use case, our system allows cookies in cases when user interaction with the widget is detected. However, blanket third-party cookie blocking is not an ideal solution, because some third-party widgets do require cookies, to authenticate with their services, for instance. Therefore, we can very simply strip these from the request without breaking the page. This is simple because most third-party cookies have no function beyond tracking. The first anti-tracking subsystem deals with protecting users from tracking cookies. The Ghostery anti-tracking system is split into two subsystems: One that handles only cookies, and the other which handles all other data sent in headers and the URL path. The latter we currently do not handle as our data shows that the reach of this method is exceptionally low however, our system allows us to continually monitor the situation, should this change. Therefore, we have three transmission vectors: HTTP Headers, URL Path, and Post data. Like existing tools, we focus on removing UIDs in transmission, rather than trying to prevent UID generation. This aims to reduce site breakage, and enable services to collect data, provided it does not compromise the user’s privacy. Our system modifies request URLs instead of blocking. It is also designed to be conservative - we only remove data which we determine to be UIDs and leave the rest alone. Therefore, we designed a system which combines local with global evaluation of tracking data. Likewise, relying on purely local evaluation of whether data is a UID or not has significant limitations. Ghostery Anti-trackingĪs we outlined in the previous section, blocklists have several drawbacks, and we did not want such an aggressive system. Thus, some kind of collaboration is required between users to determine what data is safe, and what is not – and this is the method Ghostery’s anti-tracking uses. In many cases we will not know if data sent is unique to us until we have tested it in another browser and seen a different value, like in the fingerprinting example in the previous post. Heuristic approaches like Privacy Badger are limited by just having local knowledge. With blocking browser extensions being used ever more ( over 40% of users for some market segments), those who write the block list would have the power to cut off a significant proportion of a company’s traffic - deservedly or not. For example, the Facebook like button is still allowed when using the EasyPrivacy blocking list, and there are many other such exceptions.īlocklists bestow significant power to their curators. On the other hand, exceptions made to prevent site breakage may then allow some privacy leaks. Overly broad blocking rules may block many requests which are of no privacy risk. Examples include Privacy Badger and Ghostery’s own anti-tracking system.īlocklist-based methods have several shortcomings:īlocking requests is very coarse grained and can easily break site functionality.
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