Method and system for biometric template protection

A system, comprising:

• a memory module storing a plurality of instructions;
• one or more communication interfaces;
• an initial perturbations generation module;
• a neural network;
• a perturbations computation and updation module;
• and
• one or more hardware processors coupled to the memory module via the one or more communication interfaces, wherein the one or more hardware processors are configured by the instructions to:
• collect a biometric template comprising at least one biometric data pertaining to a user, as an input;
• generate and assign a first binary code (BC) to a class of the biometric data in the biometric template, by the initial perturbations generation module;
• generate a second binary code (BC′) by collecting an initial random perturbation and a plurality of feature vectors pertaining to the at least one biometric data as input, for the neural network;
• till the BC′ is at least equal to the BC:
• compare the BC and the BC′, for the perturbations computation and updation module;
• compute perturbations as a function of gradients of the neural network, based on a an error generated at the perturbations computation and updation module for the BC and the BC′;
• process the computed perturbations and the initial random perturbation to generate a cumulative perturbation;
• and
• update the BC′ based on the plurality of feature vectors and the cumulative perturbations;
• and
• when the BC′ is equal to the BC:
• compute value of final perturbation as equal to the cumulative perturbation;
• and
• map the final perturbation and the plurality of feature vectors to the first binary code.

A non-transitory computer readable medium biometric data protection, comprising:

• collecting a biometric template comprising at least one biometric data pertaining to a user, as an input, via one or more hardware processors;
• generating and assigning a first binary code (BC) to a class of the biometric data in the biometric template, via the one or more hardware processors;
• generating a second binary code (BC′) by collecting an initial random perturbation and a plurality of feature vectors pertaining to the at least one biometric data as input, via the one or more hardware processors, by a neural network of a system;
• till BC′ is at least equal to BC:
• comparing BC and BC′, via the one or more hardware processors, by a perturbations computation and updation module of the system;
• computing perturbations as a function of gradients of the neural network, based on an error generated at the perturbations computation and updation module for BC and BC′, via the one or more hardware processors;
• processing the computed perturbations and the initial random perturbation to generate a cumulative perturbation, via the one or more hardware processors;
• and
• updating BC′ based on the plurality of feature vectors and the cumulative perturbations;
• and
• when BC′ is equal to BC:
• computing value of final perturbation as equal to the cumulative perturbation;
• and
• mapping the final perturbation and the plurality of feature vectors to the first binary code.