CS406: Information Security

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.