Abstract: A system and method for classification of voice samples to genuine voice samples or spoofing voice samples may include: extracting a set of features from each of a plurality of voice samples, each voice sample labeled as genuine or spoof; training a neural network having a plurality of nodes organized into layers, with links between the nodes, wherein each link comprises a weight, with the sets of features, by adjusting at least one of the weights using a loss function that comprises a regulation factor, wherein the regulation factor is set to zero for voice samples labeled as genuine and is proportional to the prediction of the neural network for data samples labeled as spoofing.