Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The increasing availability and use of biometric data leads to situations when sensitive biometric data is to be handled by entities who may not be fully trusted or otherwise are not authorized to have full access to such data. This calls for mechanisms of provably protecting biometric data while still allowing the computation to take place. Our focus is on privacy-preserving matching of two fingerprints authentication or identification purposes using traditional minutia-based representation of fingerprints that leads to the most discriminative fingerprint comparisons. Unlike previous work in the security literature,  would like to focus on algorithms that are guaranteed to find the maximum number of minutiae that can be paired together beten two fingerprints leading to more accurate comparisons. To address this problem,  formulate it as a flow network problem and reduce it to finding maximum matching size in bipartite graphs. The resulting problem is in turn reduced to computing the rank of a non-invertible matrix, formed as a randomized adjacency matrix of the bipartite graph.  then provide data-oblivious algorithms for matrix rank computation and consecutively finding maximum matching size in a bipartite graph and also extend the algorithms to solve the problem of accurate fingerprint matching. These algorithms lead to their secure counterparts using standard secure two-party or multi-party techniques. Lastly,  implement secure fingerprint matching in the secure two-party computation setting using garbled circuit evaluation. Our experimental results demonstrate that the techniques are efficient, leading to performance similar to that of other fastest secure fingerprint matching techniques, despite higher complexity of our solution that higher accuracy demands.
['Marina Blanton', 'Siddharth Saraph']
I am writing a research paper on a idea Oblivious Maximum Bipartite Matching Size Algorithm with Applications to Secure Fingerprint Identification
[{"from": "human", "value": "I am writing a research paper on a idea Oblivious Maximum Bipartite Matching Size Algorithm with Applications to Secure Fingerprint Identification"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The increasing availability and use of biometric data leads to situations when sensitive biometric data is to be handled by entities who may not be fully trusted or otherwise are not authorized to have full access to such data. This calls for mechanisms of provably protecting biometric data while still allowing the computation to take place. Our focus is on privacy-preserving matching of two fingerprints authentication or identification purposes using traditional minutia-based representation of fingerprints that leads to the most discriminative fingerprint comparisons. Unlike previous work in the security literature,  would like to focus on algorithms that are guaranteed to find the maximum number of minutiae that can be paired together beten two fingerprints leading to more accurate comparisons. To address this problem,  formulate it as a flow network problem and reduce it to finding maximum matching size in bipartite graphs. The resulting problem is in turn reduced to computing the rank of a non-invertible matrix, formed as a randomized adjacency matrix of the bipartite graph.  then provide data-oblivious algorithms for matrix rank computation and consecutively finding maximum matching size in a bipartite graph and also extend the algorithms to solve the problem of accurate fingerprint matching. These algorithms lead to their secure counterparts using standard secure two-party or multi-party techniques. Lastly,  implement secure fingerprint matching in the secure two-party computation setting using garbled circuit evaluation. Our experimental results demonstrate that the techniques are efficient, leading to performance similar to that of other fastest secure fingerprint matching techniques, despite higher complexity of our solution that higher accuracy demands."}]