About Real-Time Device Fingerprinting Solutions

Identify users based on the specific characteristics of their devices, such as screen resolution and touch support, software configurations like operating system version and installed plugins and extensions and other device-specific attributes, to build accurate, robust fingerprints.
This View more now is analyzed to detect patterns that are unique to each device and may be indicative of fraudulent activity or other risky behavior. Using a range of advanced detection methods and threat intelligence, the fingerprints are compared against previously stored fingerprints in order to determine whether the incoming device has been recognized or is exhibiting suspicious activity.

The data points collected are then normalized (transformed into a standard format so they are directly comparable) and relevant features or attributes are extracted. These can include hardware-related data such as the device model and CPU details; software-related data such as installed fonts and browser plugins and extensions; or other device-specific attributes like time zone settings and language preferences.

Real-Time Device Fingerprinting Solutions for Proactive Protection

Once the feature data is gathered, an algorithm is used to create a fingerprint that represents the device or browser. The fingerprint is then stored on the server side for future comparisons against incoming device interactions.

Choosing the best device fingerprinting solution requires consideration of multiple factors, including integration with existing systems, data normalization and continuous monitoring and updates. Open-source fingerprinting solutions CreepJS, FingerprintJS and Castle are currently the most well maintained and easy to use for developers. Commercial alternatives, like Seon, are known for their aggregations and identity enrichment, which can be particularly effective for combatting bots and advanced fraud techniques.