CS406: Information Security

Each sensor decides whether the user is legitimate or not by returning either accept or reject. The MFA system then combines the collected results and provides a group decision based on the resulting vector. Hence, it is possible to utlize the threshold decision functions or weighted threshold functions depending on the reliability of the sensor. For the first case, the sensor will return the value $z_{i}, z_{i}=[0 ; 1]$, which could be interpreted as either YES or NO. Then, the conditional probabilities $P\left(z_{i} \mid H_{0}\right)$ and $P\left(z_{i} \mid H_{1}\right)$ are defined by $F A R_{i}$ and $F R R_{i}$ values, respectively, for $i$ -th sensor. Here, $F A R_{i}$ and $F R R_{i}$ are taken at the CER/EER point, e . g ., $z_{i}$ is selected at the point where $F A R_{i}=F R R_{i}$. Generally, this methodology reflects the scenarios of ownership or knowledge factors from the biometric perspective.