Extracting the Electric Network Frequency (ENF) fluctuations from an audio recording and comparing it to a reference database is a new approach in performing forensic digital audio authentication. The problem statement of the IEEE SP cup 2016 competition relates to time-varying location-dependent signature of power grids as it becomes intrinsically captured in media recordings, due to direct or indirect influences from the respective power grid. In this project signal processing and information security/forensics are collectively elaborated.
The objective of this project is to implement and design a range of programs and algorithms for capturing and extracting ENF signals for a novel ENF based application. Without relying on the availability of concurrent power references, an ENF pattern extracted from a given digital recording was examined to infer the power grid in which the recording was done. The statistical features of ENF pattern variations for this region-of recording-identification process were exploited. With these features a multiclass SVM classifier, which is able to identify the grid of recording of a given signal, was implemented. The latter part of the project involves with circuit design and data analysis for ENF acquisition.
A Graphical User Interface (GUI) was developed to display the most probable three, grid-of-origins for a given recording. The whole process was tested and evaluated for the test data.