Multifactor Authentication

The sensor responds with a result of its measurements as well as a probabilistic characteristics. Further, the data is merged before the final decision is made. Therefore, the entire set of the measured data could be utilized when making a group decision and, accordingly, a common result might be established based on the set collected from all sensors.

In the second case, the sensor returns a result of the measurements as well as the template comparison in the form of a match score \(z_{i}\) \((0 \leq z_{i} \leq 1)\). For each of the values \(z_{i}\), the conditional probability \(P\left(z_{i} \mid H_{0}\right)\) is calculated based on the \(F A R_{i}\) values at \(z_{i}\). In addition, the conditional probability \(P\left(z_{i} \mid H_{1}\right)\) is determined by \(F R R_{i}\) values at \(z_{i}\).

This approach offers an opportunity to consider the strict decision methodology as a simplified model of the probabilistic one for the case where \(F A R_{i}\) and \(F R R_{i}\) are given only in one point. Here, the measurement result can only take two values, i.e., higher or lower than the selected threshold.