Empirical Evaluation of ENF Extraction Methods for Accurate Timestamping in Multimedia Forensics

The extraction of electrical network frequency (ENF) data from audio signals has become a key tool in multimedia forensics, enabling applications such as timestamping, authentication, and geolocation estimation. In particular, timestamping of audio recordings can be performed by extracting the ENF signal and correlating the result with reference records. In this paper, we present a comparative analysis of ENF-based methods for accurate timestamping of audio recordings using real-world data from various sources. We analyze the accuracy of these methods in estimating the timestamps of the records. We compare the influence of different parameters, such as the duration of the target signal and the reference signal, and the use of different correlation metrics. In addition, we provide a robust platform for the empirical evaluation of the ENF extraction methods and the features of the target-reference correlation approach. Our results offer several insights and practical recommendations for optimizing ENF-based timestamping approaches.