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Identity impersonation in higher education exams is an old and widespread cheating phenomenon that builds incompetent graduates. In the world of artificial intelligence, there should be no place for cheating in exams. Due to the unique nature of fingerprints, where every person has a unique fingerprint, biometric authentication is a good option to prevent spoofing in university exams. In this paper, we propose an intelligent and secure fingerprint authentication model. The smart model is based on SIFT feature detection and the KNN algorithm for fingerprint matching. For experimental evaluation, we use the SOCOFing dataset, which shows good results. This makes our model ideal for preventing impersonation.
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DOI: 10.1145/3659677.3659720
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