Determination of time of recording with Electric Network Frequency (ENF)

1. Determination of time of recording with Electric Network Frequency (ENF) M.P. Huijbregtse BS, Zeno Geradts PhD AAFS Denver 2009 Nederlands Forensisch Instituut Laan van Ypenburg 6, 2497 GB Den Haag

2. Outline • Introduction ENF • Implications • Research • Conclusions

3. Conclusions Introduction Implications Research Introduction Electricity network • Alternating current • Frequency • Europe 50 Hz • United States 60 Hz

4. Conclusions Introduction Implication Research Introduction ENF pattern

5. Conclusions Introduction Implication Research Introduction – prior research • C. Grigoras, 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) • M. Kajstura, A Trawinska, J. Hebestreit, Application of the Electrical Network Frequency (ENF) Criterion – A case of a Digital Recording, Forensic Science International, vol. 155, pp. 165-171 (2005) • A.J. Cooper, The electric network frequence (ENF) as an aid to authenticating forensic digital audio recordings – an automated approach, Conference paper, AES 33rd International Conference, USA (2008)

6. Conclusions Introduction Implication Research Introduction

7. Conclusions Introduction Implication Research Introduction

8. Conclusions Introduction Implication Research Introduction • Conditions: • ENF pattern is the same in the whole network • ENF pattern is “unique” • ENF pattern can be filtered from a recorder

9. Conclusions Introduction Implication Research Implications – build a database

10. Conclusions Introduction Implication Research Implications – Build database

11. Conclusions Introduction Implication Research Implications Build a database

12. Conclusions Introduction Implication Research Software • Matlab • Java- applet for collecting, developed by us : www.sourceforge.net enf collector

13. Software

14. Downsampling naar 300 Hz Bandpass filteren rond 50 Hz Spectrogram maken Piek frequenties bepalen Conclusions Introduction Implication Research Implications - filter

15. Conclusions Introduction Implication Research Implications – Filter signal Spectrogram:

16. Conclusions Introduction Implication Research Implications – filter signal

17. Conclusions Introduction Implication Research Implications – filter signal

18. Conclusions Introduction Implications Research Research - Questions • How unique is an ENF pattern ? • Is it possible to determine the time of recording ?

19. Conclusies Introductie Praktisch Onderzoek Implication Matching root mean square:

20. Conclusions Introduction Implications Research Implication - Uniqueness

21. Conclusions Introduction Implications Research Implication - Uniqueness

22. Conclusions Introduction Implications Research Implication best match • Recording of 3600 seconds:0.053 Hz < 0.080 Hz • Recording of 600 seconds:0.047 Hz > 0.040 Hz (!) • Recording of 60 seconds :0.015 Hz > 0.007 Hz (!)

23. Conclusions Introduction Implications Research Implication – Best match

24. Conclusions Introduction Implications Research Implication – Best match

25. Conclusions Introduction Implications Research Second method Correlationcoefficiënt:

26. Conclusions Introduction Implications Research Implication – best match

27. Conclusions Introduction Implications Research Conclusions • As in literature: • ENF pattern is the same in the whole network • ENF pattern can be extracted from network • Suggestions: • Matching of short recording (< 600 seconds) false hits are possible • Matching with the correlation coefficent better than root mean square error

28. Future research • Different recorders • (MP3) compression • Improvement of the current method