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The conventional authentication technologies, like RFID tags andauthentication cards/badges, suffer from different weaknesses, therefore aprompt replacement to use biometric method of authentication should be appliedinstead. Biometrics, such as fingerprints, voices, and ECG signals, are uniquehuman characters that can be used for authentication processing. In this work,we present an IoT real-time authentication system based on using extracted ECGfeatures to identify the unknown persons. The Discrete Cosine Transform (DCT)is used as an ECG feature extraction, where it has better characteristics forreal-time system implementations. There are a substantial number of researcheswith a high accuracy of authentication, but most of them ignore the real-timecapability of authenticating individuals. With the accuracy rate of 97.78% ataround 1.21 seconds of processing time, the proposed system is more suitablefor use in many applications that require fast and reliable authenticationprocessing demands.

An IoT Real-Time Biometric Authentication System Based on ECG Fiducial Extracted Features Using Discrete Cosine Transform