However, blanket third-party cookie blocking is not an ideal solution, because some third-party widgets do require cookies, to, for instance, authenticate with their service. Therefore we can very simply strip these from the request without breaking the page.

This is because the vast majority of third-party cookies have no function beyond tracking. Protecting from tracking cookies is relatively simple. One that handles only Cookies, and the other which handles all other data sent in headers and the URL path. The Ghostery anti-tracking system is split into two subsystems. The latter we currently do not handle as our data shows that the reach of this method is very 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 purely local evaluation of whether data is a UID or not has significant limitations.

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.Īs we outlined in the previous section, blocklists have several drawbacks, and we did not want such an aggressive system. 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. Tracking companies can constantly change their URLs, domains and methods to prevent blocking, and those generating the lists must respond in each case.įinally, blocking lists bestow significant power to their curators. Secondly, as these lists are manually maintained, they will always be playing catchup against trackers. On the other side, exceptions made to prevent site breakage may then allow some privacy leaks, for example the Facebook like button is still allowed when using the EasyPrivacy blocking list, and there are many other such exceptions. Overly broad blocking rules may block many requests which are of no privacy risk. Firstly, blocking requests is very coarse grained and can easily break site functionality. Examples include Privacy Badger and Ghostery’s own anti-tracking system.īlocklist-based methods have several shortcomings.

Heuristic/algorithm-based: These tools use heuristic and/or algorithmic analysis to determine when to block or modify requests.

Examples include Ghostery, Disconnect, Firefox tracking protection, and uBlock Origin. This predominately targets advertising trackers as an extension or side-effect to Adblocking features.

Blocklist-based: These tools use curated blocklists in order to block third parties seen to be tracking.

These can be categorized into two groups: In general these act as browser extensions which monitor network traffic and intervene when tracking is detected, i.e. There are already many tools available which aim to prevent the kinds of tracking we have described.

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