Authors: Lilei Zheng, Ying Zhang, Chien Eao Lee, Vrizlynn Thing
DFRWS USA 2017
This work addresses the problem of ENF pattern matching in the task of time-of-recording estimation. Inspired by the principle of visual comparison, we propose a novel similarity criterion, the bitwise similarity, for measuring the similarity between two ENF signals. A search system is then developed to find the best matches for a given test ENF signal within a large searching scope on the reference ENF data. By empirical comparison to other popular similarity criteria, we demonstrate that the proposed method is more effective and efficient than the state-of-the-art. For example, compared with the recent DMA algorithm, our method achieves a relative error rate decrease of 86.86% (from 20.32% to 2.67%) and a speedup of 45 faster search response (41.0444 s versus 0.8973 s). Last but not least, we present a strategy of uniqueness examination to help human examiners to ensure high precision decisions, which makes our method practical in potential forensic use.