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There are growing concerns about the privacy invasion of the biometric technology. This is due to the fact that biometric characteristics are immutable and hence their compromise is permanent. Thus, reissuable biometrics was devised to denote biometric templates that can be reissued and replaced. Biometric Strengthening is a form of reissuable biometrics which strengthens the biometric templates by altering their original values thru the Gaussian distribution, thus generating a new set of values. However, the main drawback of Biometric Strengthening is its great degradation in performance when the legitimate token is stolen and used by the imposter to claim as the legitimate user. In this paper, we employ the probabilistic neural network (PNN) as the classifier to alleviate this problem. The compatibility of Biometric Strengthening with PNN is discussed, along with the experiments that are tested on our own independent offline signature data set.