For example a fingerprint reader would produce a

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or if the user’s physical features are obscured. For example, a fingerprint reader would produce a false rejection if the user’s fingers were covered in dirt or grease, obscuring the characteristics of the fingerprint. False rejections are referred to as Type I errors .
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CHAPTER 9 | Physical Security and Access Control 191 9 Physical Security and Access Control Crossover Error Rate The crossover error rate (CER) is the point at which Type I errors and Type II errors are equal, as shown in Figure 9-2. All biometric systems can be calibrated to reduce either the false acceptance or false rejection rates to near zero. Unfortunately, calibrating the system to reduce or eliminate Type I errors generally raises the rate of Type II errors. A biometric system could be calibrated such that the sensitivity is turned all the way down, so that it accepts everyone. Of course, this would produce a large number of false positives, but zero false negatives. Likewise, the sensitivity could be turned all the way up so that the system doesn’t accept anyone, eliminating the false positives but producing a large number of false negatives. The CER is an accurate way to compare the real accuracy of various biometric systems. The smaller the CER, the more accurate it is. In other words, a system with a CER of 3 percent is more accurate than one with a CER of 5 percent. Failure to Enroll Rate All biometric systems require subjects to enroll, or present sample data, before they can use the system. As with any system, things do not always work the way they should and the sample data can be lost. The percentage of failed attempts to create a sample data set for an individual, divided by the total number of attempts to enroll users is called the failure to enroll rate . Failure to Capture Rate Failure to capture, also referred to as failure to acquire, is the percentage of failed attempts to authenticate to the system. This number describes the failure of the system to acquire the necessary data from an individual to make an accept or reject decision. This is most often caused by a dirty or smudged scanning device or user error. Biometric System Sensitivity Crossover Error Rate (CER) False Acceptance Rate (Type II) False Rejection Rate (Type I) FIGURE 9-2 Crossover error rate.
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192 PART 2 | Mitigating Risk with Access Control Systems, Authentication, and PKI Modes of Operation Biometric systems are used for two primary purposes: verification of an individual’s stated identity and ascertaining the identity of an unknown user. Verification In verification mode , a biometric system makes a simple one-to-one comparison and returns a binary result. The individual presents a claim of identity—a token or user name, for example—and a biometric sample such as a fingerprint or retinal scan. The access control system simply retrieves the known user record for the claimed identity from a database, and then compares that to the sample data provided by the individual. If the two data sets match, the user is authenticated and the system returns a positive result.
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  • Winter '15
  • DennisBackherms

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