Web Tracking Methods/Analysis/Mitigation

CloneRanger · Nov 7, 2015

Technical analysis of client identification mechanisms

In common use, the term “web tracking” refers to the process of calculating or assigning unique and reasonably stable identifiers to each browser that visits a website. In most cases, this is done for the purpose of correlating future visits from the same person or machine with historical data.

Some uses of such tracking techniques are well established and commonplace. For example, they are frequently employed to tell real users from malicious bots, to make it harder for attackers to gain access to compromised accounts, or to store user preferences on a website. In the same vein, the online advertising industry has used cookies as the primary client identification technology since the mid-1990s. Other practices may be less known, may not necessarily map to existing browser controls, and may be impossible or difficult to detect. Many of them - in particular, various methods of client fingerprinting - have garnered concerns from software vendors, standards bodies, and the media.

To guide us in improving the range of existing browser controls and to highlight the potential pitfalls when designing new web APIs, we decided to prepare a technical overview of known tracking and fingerprinting vectors available in the browser. Note that we describe these vectors, but do not wish this document to be interpreted as a broad invitation to their use. Website owners should keep in mind that any single tracking technique may be conceivably seen as inappropriate, depending on user expectations and other complex factors beyond the scope of this doc.

We divided the methods discussed on this page into several categories: explicitly assigned client-side identifiers, such as HTTP cookies; inherent client device characteristics that identify a particular machine; and measurable user behaviors and preferences that may reveal the identity of the person behind the keyboard (or touchscreen). After reviewing the known tracking and fingerprinting techniques, we also discuss potential directions for future work and summarize some of the challenges that browser and other software vendors would face trying to detect or prevent such behaviors on the Web.

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Nevertheless, we feel that the remaining signals - such as clock skew and drift and the network-level and user-specific signals described later on - are together likely more than sufficient to uniquely identify virtually all users.

https://www.chromium.org/Home/chromium-security/client-identification-mechanisms
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Worth reading the full article, & checking out the links in it

Rasheed187 · Nov 8, 2015

Thanks, will read it later, looks interesting.

deBoetie · Nov 8, 2015

Excellent articles and references. If somewhat dismal, at least keeps a person humble.

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Web Tracking Methods/Analysis/Mitigation

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