Device fingerprinting techniques are used by websites, online services, and app developers to identify devices and browsers, detect suspicious activity, and personalize user experiences. However, they can be vulnerable to privacy breaches and security vulnerabilities if not implemented properly.
As a result, it’s important to understand how these methods work and the limitations of their use before integrating them into your site or service. This article will explore some of the most popular device fingerprinting techniques, as well as their pros and cons, to help you make an informed decision about which approach is right for your needs.
The basic idea behind device fingerprinting is that each unique combination of hardware attributes can be matched against a list of known fraudulent patterns or blacklisted attributes. This enables e-commerce platforms to identify high-risk orders, flag them for manual review, or even block the transaction altogether. For example, if an order comes from a device with a known fraud pattern or has been associated with other suspicious devices, the platform can flag it for investigation and request additional authentication to verify the user’s identity.
To create a device fingerprint, a website or service collects device intelligence from the browser, such as the operating system, version, and screen resolution; installed fonts and plugins; and IP address. This data is compiled into a single identifier, called a device hash. The more data points that a fingerprint contains, the more accurate it will be as an identifier. It’s important to remember, though, that the device hashes are only as accurate as the data sources from which they are collected. For example, there’s more than one person in the world using a MacBook Pro with Firefox, so a device fingerprint will only be as reliable as that data set.
One of the major drawbacks of fingerprinting is that it’s a relatively easy technique for hackers to spoof or evade. For example, by simply changing their browser’s user agent or by using a VPN or private browsing mode, attackers can effectively hide their device information from fingerprinting.
Another challenge is that fingerprinting requires the collection of sensitive user data, which can raise concerns about privacy and regulatory compliance. To mitigate these issues, e-commerce platforms should only use device fingerprinting as an additional method of fraud prevention and not as the sole method of tracking or identifying users.
For developers who want to experiment with device fingerprinting but don’t have the budget for a commercial solution, open-source solutions offer a cost-effective and accessible entry point. While they may lack the more advanced capabilities (such as machine learning and network effects) of their commercial counterparts, they do provide greater transparency into the fingerprinting process and are generally easier to customize. Additionally, they are regularly updated and maintained to stay ahead of changes to privacy controls and browser initiatives.