Biometric Error Rate
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Cost And Error Rates Of Standard Biometrics
News Events Blog My Reports Register June 23, 2015 Bob Lockhart In crossover error rate biometrics Biometrics, Which Error Rate Matters? Biometrics error rates are like wine. The question, “What is a good wine?” cannot
Equal Error Rate Biometrics
be answered out of context. Not for me, at least. I need more information like, “What are you eating with it?” I might not suggest the same wine for a rack fingerprint biometrics of lamb as I would for a filet of sole. Biometrics’ wine question is, “What is the most important error rate?” Again, it depends on what you’re doing. Three error rates are commonly discussed relating to biometrics: the false accept rate, the false reject rate, and the equal error rate (or crossover error rate): the point where a biometrics’ false accept rate and equal error rate calculation false reject rates are equal. Vendors can tune their false accept and false reject rates: for example, by adjusting the size of their biometric templates or by adjusting the confidence interval that determines a match. Biometric verification is a statistical process, not a yes/no comparison, so a more precise comparison produces a greater degree confidence in the verification. You might think that a greater confidence interval is better but that is not always the case. Like most everything in biometrics, error rate selection is governed by use cases. For starters, we can dismiss the equal error rate (EER). In all my research, I have yet to encounter a use case where having an equal probability of false accept or false reject was optimal. EER is an interesting academic construct but it’s hard to think of a use case where it matters. That leaves us with choosing the right false accept or false reject rate, and with choosing the right wine for our rack of lamb. A greater confidence interval lowers the probability of a false positive: that someone will be accepted who should not be accepted. T
Disney World in Lake Buena Vista, Florida, biometric measurements are taken from the fingers of guests to ensure that a ticket is used by
Equal Error Rate Roc
the same person from day to day Biometrics refers to metrics crossover error rate calculation related to human characteristics. Biometrics authentication (or realistic authentication)[note 1] is used in computer science as a
Biometrix
form of identification and access control.[1] It is also used to identify individuals in groups that are under surveillance. Biometric identifiers are the distinctive, measurable characteristics used to label https://www.tractica.com/biometrics/in-biometrics-which-error-rate-matters/ and describe individuals.[2] Biometric identifiers are often categorized as physiological versus behavioral characteristics.[3] Physiological characteristics are related to the shape of the body. Examples include, but are not limited to fingerprint, palm veins, face recognition, DNA, palm print, hand geometry, iris recognition, retina and odour/scent. Behavioral characteristics are related to the pattern of behavior of a person, https://en.wikipedia.org/wiki/Biometrics including but not limited to typing rhythm, gait, and voice.[4][note 2] Some researchers have coined the term behaviometrics to describe the latter class of biometrics.[5] More traditional means of access control include token-based identification systems, such as a driver's license or passport, and knowledge-based identification systems, such as a password or personal identification number.[2] Since biometric identifiers are unique to individuals, they are more reliable in verifying identity than token and knowledge-based methods; however, the collection of biometric identifiers raises privacy concerns about the ultimate use of this information.[2][6] The biometrics market was expected to be worth $13.8 billion in 2015.[7] Contents 1 Biometric functionality 2 Multimodal biometric system 3 Performance 4 History of biometrics 5 Adaptive biometric systems 6 India's national ID program 7 Recent advances in emerging biometrics 7.1 Operator signatures 7.2 Proposed requirement for certain public networks 8 Issues and concerns 8.1 Human Dignity 8.2 Privacy and discrimination 8.3 Danger to owners of secured items 8.4 Cancelable biometrics 8.5 Soft biometrics 8.6 International sharing of biom
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as a match by the system. A False Reject is when a matching pair of biometric data is wrongly rejected by the system. The two errors are complementary: When you try to lower one of the errors by varying the threshold, the other error rate automatically increases. There is therefore a balance to be found, with a decision threshold that can be specified to either reduce the risk of FAR, or to reduce the risk of FRR. In a biometric authentication system, the relative false accept and false reject rates can be set by choosing a particular operating point (i.e., a detection threshold). Very low (close to zero) error rates for both errors (FAR and FRR) at the same time are not possible. By setting a high threshold, the FAR error can be close to zero, and similarly by setting a significantly low threshold, the FRR rate can be close to zero. A meaningful operating point for the threshold is decided based on the application requirements, and the FAR versus FRR error rates at that operating point may be quite different. To provide high security, biometric systems operate at a low FAR instead of the commonly recommended equal error rate (EER) operating point where FAR = FRR. Compromised biometric data Paradoxically, the greatest strength of biometrics is at the same time its greatest liability. It is the fact that an individual's biometric data does not change over time: the pattern in your iris, retina or palm vein remain the same throughout your life. Unfortunately, this means that should a set of biometric data be compromised, it is compromised forever. The user only has a limited number of biometric features (one face, two hands, ten fingers, two eyes). For authentication systems based on physical tokens such as keys and badges, a compromised token can be easily canceled and the user can be assigned a new token. Similarly, user IDs and passwords can be changed as often as required. But if the biometric data are compromised, the user may quickly run out of biometric features to be used for authentication. Vulnerable points of a biometric