We’ve talked about Levels 1 and 2 of iBeta’s confirmation that particular biometric implementations meet the requirements of ISO 30107-3. But now with Yoti’s confirmation, we can talk about iBeta Level 3.
“The test method was to apply 1 bona fide subject presentation that alternated with 3 artefact presentations such that the presentation of each species consisted of 150 Presentation Attacks (PAs) and 50 bona fide presentations, or until 56 hours had passed per species. The results were displayed for the tester on the device as “Liveness check: Passed” for a successful attempt or “Liveness check: Failed” for an unsuccessful attempt.
“iBeta was not able to gain a liveness classification with the presentation attacks (PAs) on the Apple iPhone 16 Pro. With 150 PAs for each of 3 species, the total number of attacks was 450, and the overall Attack Presentation Classification Error Rate (APCER) was 0%. The Bona Fide Presentation Classification Error Rate (BPCER) was also calculated and may be found in the final report.
“Yoti Limited’s myface12122025 application and supporting backend components were tested by iBeta to the ISO 30107-3 Biometric Presentation Attack Detection Standard and found to be in compliance with Level 3.”
“Yoti’s MyFace is the first passive, single-selfie liveness technology in the world to conform to iBeta’s Level 3 testing under ISO/IEC 30107-3 – their highest level for liveness checks.”
When marketing your facial recognition product (or any product), you need to pay attention to your positioning and messaging. This includes developing the answers to why, how, and what questions. But your positioning and your resulting messaging are deeply influenced by the characteristics of your product.
If facial recognition is your only modality
There are hundreds of facial recognition products on the market that are used for identity verification, authentication, crime solving (but ONLY as an investigative lead), and other purposes.
Some of these solutions ONLY use face as a biometric modality. Others use additional biometric modalities.
Similarly, a face-only company will argue that facial recognition is a very fast, very secure, and completely frictionless method of verification and authentication. When opponents bring up the demonstrated spoofs against faces, you will argue that your iBeta-conformant presentation attack detection methodology guards against such spoofing attempts.
Of course, if you initially only offer a face solution and then offer a second biometric, you’ll have to rewrite all your material. “You know how we said that face is great? Well, face and gait are even greater!”
It seems that many of the people that are waiting the long-delayed death of the password think that biometrics is the magic solution that will completely replace passwords.
For this reason, your company might have decided to use biometrics as your sole factor of identity verification and authentication.
Or perhaps your company took a different approach, and believes that multiple factors—perhaps all five factors—are required to truly verify and/or authenticate an individual. Use some combination of biometrics, secure documents such as driver’s licenses, geolocation, “something you do” such as a particular swiping pattern, and even (horrors!) knowledge-based authentication such as passwords or PINs.
This naturally shapes your positioning and messaging.
The single factor companies will argue that their approach is very fast, very secure, and completely frictionless. (Sound familiar?) No need to drag out your passport or your key fob, or to turn off your VPN to accurately indicate your location. Biometrics does it all!
The multiple factor companies will argue that ANY single factor can be spoofed, but that it is much, much harder to spoof multiple factors at once. (Sound familiar?)
So position yourself however you need to position yourself. Again, be prepared to change if your single factor solution adopts a second factor.
A final thought
Every company has its own way of approaching a problem, and your company is no different. As you prepare to market your products, survey your product, your customers, and your prospects and choose the correct positioning (and messaging) for your own circumstances.
And if you need help with biometric positioning and messaging, feel free to contact the biometric product marketing expert, John E. Bredehoft. (Full-time employment opportunities via LinkedIn, consulting opportunities via Bredemarket.)
In the meantime, take care of yourself, and each other.
Well, the FATE side of the house has released its first two studies, including one entitled “Face Analysis Technology Evaluation (FATE) Part 10: Performance of Passive, Software-Based Presentation Attack Detection (PAD) Algorithms” (NIST Internal Report NIST IR 8491; PDF here).
Latent prints are usually produced by sweat, skin debris or other sebaceous excretions that cover up the palmar surface of the fingertips. If a latent print is on the glass platen of the optical sensor and light is directed on it, this print can fool the optical scanner….
Capacitive sensors can be spoofed by using gelatin based soft artificial fingers.
There is another weakness of these types of readers. Some professions damage and wear away a person’s fingerprint ridges. Examples of professions whose practitioners exhibit worn ridges include construction workers and biometric content marketing experts (who, at least in the old days, handled a lot of paper).
The solution is to design a fingerprint reader that not only examines the surface of the finger, but goes deeper.
The specialty of multispectral sensors is that it can capture the features of the tissue that lie below the skin surface as well as the usual features on the finger surface. The features under the skin surface are able to provide a second representation of the pattern on the fingerprint surface.
Multispectral sensors are nothing new. When I worked for Motorola, Motorola Ventures had invested in a company called Lumidigm that produced multispectral fingerprint sensors; they were much more expensive than your typical optical or capacitive sensor, but were much more effective in capturing true fingerprints to the subdermal level.
“Gelatin based soft artificial fingers” aren’t the only way to fool a biometric sensor, whether you’re talking about a fingerprint sensor or some other sensor such as a face sensor.
Regardless of the biometric modality, the intent is the same; instead of capturing a true biometric from a person, the biometric sensor is fooled into capturing a fake biometric: an artificial finger, a face with a mask on it, or a face on a video screen (rather than a face of a live person).
This tomfoolery is called a “presentation attack” (becuase you’re attacking security with a fake presentation).
And an organization called iBeta is one of the testing facilities authorized to test in accordance with the standard and to determine whether a biometric reader can detect the “liveness” of a biometric sample.
(Friends, I’m not going to get into passive liveness and active liveness. That’s best saved for another day.)
[UPDATE 4/24/2024: I FINALLY ADDRESSED THE DIFFERENCE BETWEEN ACTIVE AND PASSIVE LIVENESS HERE.]
Multispectral liveness
While multispectral fingerprint readers aren’t the only fingerprint readers, or the only biometric readers, that iBeta has tested for liveness, the HID Global Lumidigm readers conform to Level 2 (the higher level) of iBeta testing.
Bredemarket 