Distil Networks has unveiled the Hi-Def Fingerprint, an augmented device fingerprinting method that identifies unique devices more accurately than standard techniques. Finding a reliable and unique method of identification has historically been a tricky endeavor. As an analogy, Distil cites the evolution of identification methods in criminology, tracing them from their roots in the development of the mugshot and the now defunct Bertillon system, through the use of physical fingerprints, to contemporary DNA analysis.
In computer science, one such early ‘fingerprint’ was the simple fingerprint, which pulled an IP address with some affiliated header information. Basic browser fingerprints improved accuracy by pulling some additional device attributes. Distil’s Hi-Def Fingerprint pulls over 200 attributes from the device, in addition to the IP address and header information, leading to vast accuracy gains.
Distil commissioned its data science team to compare the accuracy of the following three device fingerprinting techniques to that of the Hi-Def Fingerprint:
- IP address only
- Simple fingerprint (IP address & Header information)
- Basic browser fingerprint (IP address & header information & Select Device attributes).
The study passed nearly 375 million device fingerprints through each technique, to illustrate how many unique devices would evade detection by standard methods and result in false positives. This reality, in turn, has made bot mitigation solutions reluctant to block devices, given their inaccuracy.
The result for the Hi-Def Fingerprint, on the other hand, was that it correctly identified all unique devices and gave no false positives.
| Fingerprinting Technique | No. of Unique Devices Identified | Pct. of False Positives |
| Hi-Def Fingerprint |
374,894,368 |
0.0% |
| Basic browser fingerprint |
313,301,312 |
16.4% |
| Simple fingerprint |
275,783,744 |
26.4% |
| IP address only |
149,945,280 |
60.0% |
Distil Networks furthers that Hi-Def Fingerprint:
- Inspects perimeter traffic to identify malicious devices and block bad bots
- The fingerprints stay with the bad bots so they cannot reconnect via random IP addresses, P2P networks, or proxies
- Comes with a “tamper proofing layer” to detect manipulation of data values within the fingerprint
- Logs known violators in a global database that is available to all Distil customers