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- W3195875877 abstract "In symmetric cryptosystems, the protection of secret keys is based on the traditional user authentication and likewise the security of the cryptosystem depends on the secrecy of the secret keys. In the event of lost, theft or infection of these secrete keys; the security of the cryptosystems would be compromised hence exposing critical information. Biometrics has been commercially used to verify user’s identity. Voice biometrics has been proven to be even more effective because it cannot be stolen in some cases like face, fingerprint or even iris biometrics. The research proves that a well-designed system will prompt an authentication question and on verification user must provide both the desired answer as well as desired matching threshold or the system ignores the user features. This research proposes a software-based architecture solution for Biometric Encryption of data using Voice Recognition that employed the Dynamic Time Warping (DTW) technique to solve the problem of speech biometric duration varying with non-linear expansion and contraction. The approach then used database to store the monolithically bind cryptographic key with the equivalent biometric hardened template of the user in such manner that identity of the key will stay hidden unless there is a successful biometric authentication by intended party. The research used the MIT mobile device speaker verification corpus (MDB) and A data set in quiet environment (QDB) for training and verifying session. Finally using the Equal Error Rate (EER) the research evaluated performance or rate at which False Acceptance Rate (FAR) and a False Rejection Rate (FRR) are equal. Therefore, according to the result it offers a better substitute method of user authentication than traditional pre-shared keys for benefit of protecting secret keys." @default.
- W3195875877 created "2021-08-30" @default.
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- W3195875877 date "2021-01-01" @default.
- W3195875877 modified "2023-09-24" @default.
- W3195875877 title "Bio-metric Encryption of Data Using Voice Recognition" @default.
- W3195875877 doi "https://doi.org/10.11648/j.acis.20210903.12" @default.
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