“Seeing” ENF: Power-Signature-Based Timestamp for Digital Multimedia via Optical Sensing and Signal Processing

Abstract

Electric Network Frequency (ENF) fluctuates slightly over time from its nominal value of 50 Hz/60 Hz. The fluctuations in ENF remain consistent across the entire power grid including when measured at physically distant geographical locations. The light intensity from such indoor lighting as fluorescent lamps and incandescent bulbs, which are connected to the power mains, varies in accordance with the ENF, and the fluctuations can be recorded using visual sensors. In this paper, mechanisms using optical sensors and video cameras to record and validate the presence of ENF fluctuations in indoor lighting are presented. Spectrogram and subspace-based signal processing techniques are applied to such recordings to extract the ENF signal by estimating its instantaneous frequencies as a function of time. A high correlation is observed between the ENF fluctuations obtained from indoor lighting and that of the ENF signal captured directly from the power mains supply. A similar mechanism is then used to demonstrate the presence of ENF signals in video recordings taken in different geographical areas. Experimental results show that ENF signals are present in visual recordings made in different geographical areas and can be used as a natural timestamp for optical sensor recordings and video surveillance recordings conducted in indoor lighting environments. Robustness of ENF fluctuation traces under strong compression and CMOS rolling shutter cameras is discussed. Applications of the ENF signal analysis to tampering detection of surveillance video recordings and forensic binding of the audio and visual track of a video are also demonstrated. An analytical model based on an autoregressive process is also developed for ENF signals, and the effectiveness of using innovation sequences from the model for timestamp verification is demonstrated.