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Today, biometric-based unlock modalities are evaluated almost solely on thebasis of False Accept Rate (FAR), a metric that defines how often amodel mistakenly accepts a randomly chosen incorrect input. While this is auseful measure, it does not provide sufficient information to evaluate how wellthe model stands up to targeted attacks.

Metrics

Android 8.1 introduces two new metrics associated with biometric unlocks thatare intended to help device manufacturers evaluate their security moreaccurately:

• Imposter Accept Rate (IAR): The chance that a biometric modelaccepts input that is meant to mimic a known good sample. For example, in theSmartLock trusted voice (voice unlock) mechanism, this would measure how oftensomeone trying to mimic a user's voice (using similar tone, accent, etc) canunlock their device. We call such attacks Imposter Attacks.
• Spoof Accept Rate (SAR): The chance that abiometric model accepts a previously recorded, known good sample. For example,with voice unlock this would measure the chances of unlocking a user's phoneusing a recorded sample of them saying: 'Ok, Google' We call such attacksSpoof Attacks.

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Of these, IAR measurements are not universally useful for all biometricmodalities. Consider fingerprint for example. An attacker could create a mold ofa user's fingerprint and attempt to use that to bypass the fingerprint sensor,which would count as a spoof attack. However, there isn't a way to mimic afingerprint that would be accepted as the user's - and so there's not a clearnotion of an imposter attack against fingerprint sensors.

SAR, however, works for every biometric modality.

Example attacks

The table below lists examples of imposter and spoof attacks for fourmodalities.

Table 1. Example attacks

See Test methodology for advice and more details onmethodologies to measure SAR and IAR for different biometrics.

Strong vs. weak unlocks

The bar for an unlock to be considered strong is a combination of the threeaccept rates - FAR, IAR, and SAR. In cases where an imposter attack does notexist, we consider only the FAR and SAR.

See the Android Compatibility DefinitionDocument (CDD) for the measures to be taken for weak unlock modalities.

Test methodology

Here we explain considerations and offer advice regarding test setups to measurespoof (SAR) and imposter acceptance rates (IAR) for biometric unlock modalities.See Metrics for more information on what these metrics meanand why they're useful.

Common considerations

While each modality requires a different test setup, there are a few commonaspects that apply to all of them.

Test the actual hardware

Collected SAR/IAR metrics can be inaccurate when biometric models are testedunder idealized conditions and on different hardware than it would actuallyappear on in a mobile device. For example, voice unlock models that arecalibrated in an anechoic chamber using a multi-microphone setup behave verydifferently when used on a single microphone device in a noisy environment. Inorder to capture accurate metrics, tests should be carried out on an actualdevice with the hardware installed, and failing that with the hardware as itwould appear on the device.

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Use known attacks

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Most biometric modalities in use today have been successfully spoofed, andpublic documentation of the attack methodology exists. Below we provide a briefhigh-level overview of test setups for modalities with known attacks. Werecommend using the setup outlined here wherever possible.

Anticipate new attacks

For modalities where significant new improvements have been made, the test setupdocument may not contain a suitable setup, and no known public attack may exist.Existing modalities may also need their test setup tuned in the wake of a newlydiscovered attack. In both cases you will need to come up with a reasonable testsetup. Please use the Site Feedback link at the bottom of this page to let usknow if you have set up a reasonable mechanism that can be added.

Setups for different modalities

Fingerprint

Face and Iris

Voice