A PUF Based Audio Fingerprint Based for Device Authentication and Tamper Location

As bioinformation authentication gains prominence, the significance of audio data in industries such as speech recognition intensifies, with audio storage becoming a pivotal concern for data protection. Existing audio tampering solutions fail to identify the producing device. This paper introduces an innovative method employing physical unclonable function (PUF) and audio features for identifying recording equipment and detecting tampered areas in judicial authentication within the Industrial Internet-of-Things (IIoT). The method comprises two components: the recording device, which generates an audio fingerprint using audio features and a PUF-determined random number seed, and the server, which registers, analyzes, and verifies the fingerprint. The unique, tamper-resistant PUF response is generated only when a server-provided challenge is initiated. The proposed audio fingerprint, evaluated using the Carioca 1 database and NXP LPC54S018-EVK-provided PUF functionality, enables varying tamper area identification accuracy and achieves 100% original device identification, resisting replay, cloning, and brute force attacks.