Electrical network frequency analysis
Electrical network frequency (ENF) analysis is a forensic science technique for validating audio recordings by comparing frequency changes in background mains hum in the recording with long-term high-precision historical records of mains frequency changes from a database. In effect the mains hum signal is treated as if it were a time-dependent digital watermark that can help identify when the recording was created, and help detect any edits in the recording.[1][2][3] Historical records of main frequency changes are kept on record f.e. by police in the german federal state of Bavaria since 2010[4].
The technology has been hailed as "the most significant development in audio forensics since Watergate."[5] However, according to a paper by Huijbregtse and Geradts, the ENF technique, although powerful, has significant limitations caused by ambiguity based on fixed frequency offsets during recording, and self-similarity within the mains frequency database, particularly for recordings shorter than 10 minutes.[6]
References
- ^ Cooper, A.J: "The electric network frequency (ENF) as an aid to authenticating forensic digital audio recordings – an automated approach"., Conference paper, AES 33rd International Conference, USA (2008)
- ^ Grigoras, C. : "Digital audio recording analysis – the electric network frequency criterion"., International Journal of Speech Language and the Law, vol. 12, no. 1, pp. 63-76 (2005)
- ^ Mateusz Kajstur, Agata Trawinska, Jacek Hebenstreit. "Application of the Electrical Network Frequency (ENF) Criterion: A case of a digital recording". Forensic Science International, Volume 155, Issue 2, Pages 165-171 (20 December 2005)
- ^ "Dem Verbrechen auf der Spur" (in German). Süddeutsche Zeitung. 2011-02-16.
- ^ Chris Williams (2010-06-01). "Met lab claims 'biggest breakthrough since Watergate'". The Register.
- ^ Maarten Huijbregtse, Zeno Geradts. "Using the ENF criterion for determining the time of recording of short digital audio recordings" (PDF). Lecture Notes In Computer Science; Vol. 5718, Proceedings of the 3rd International Workshop on Computational Forensics, 2009.
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