Abstract
Video
dosyalarının Elektrik Şebeke Frekansı (Electric Network Frequency - ENF)
temelli adli kanıt analizi tekniği, çoklu ortam dosyalarının kayıt zamanını
doğrulamada ve dosyalarda yapılan sahteciliği tespit etmede son yıllarda
önerilmiş en önemli araçlardan biridir. ENF, şebekede üretilen toplam gücün
tüketilen toplam güce göre artıp azalmasına bağlı olarak nominal değer
(Avrupa’da 50 Hz) etrafında sürekli salınımlar yapar. Bu salınımlar aynı şebeke
üzerindeki her noktada aynıdır. Elektrik şebekesinden beslenen bir ışık
kaynağının yaymış olduğu aydınlatma şiddeti elektrik şebeke frekansına bağlı
olarak insan gözünün fark edemeyeceği anlık değişkenlikler gösterir. Işık
şiddetindeki bu değişimler, video kameralar tarafından yakalanabilmektedir. Çekilen
videolardaki tüm resim çerçeveleri boyunca değişmeyen içerik analiz edilerek aydınlatma
şiddetinin değişim hızı, dolayısıyla elektrik şebeke frekansı kestirilebilir. Videolardan
kestirimi yapılan ENF sinyalinin, elektrik şebekesinden doğrudan elde edilen
referans ENF sinyali ile benzerlikleri hesaplanarak dosya kayıt zamanı
bilgisine ulaşılabilir. Bu çalışmada, şebeke elektriğine bağlı ışık kaynağı
türünün, CCD sensörlü kamera ile çekilmiş videolardan kestirilen ENF sinyali
kalitesinde ne derece etkili olduğu incelenmiştir. Işık kaynağı türüne göre, çeşitli
uzunluktaki videolarda ENF temelli kayıt zamanı doğrulama performansı analiz
edilmiştir.
Keywords
ENF elektrik şebeke frekansı videolarda adli kanıt video kayıt zamanı doğrulama ışık kaynağı etkisi
References
- Bollen, M. H., ve Gu, I. (2006) Signal Processing of Power Quality Disturbances. Wiley.
- Chai, J., Liu, F., Yuan, Z., Conners, R., ve Liu, Y. (2013) Source of ENF in Battery-Powered Digital Recordings, Audio Engineering Society Convention 135.
- Cooper, A. (2008) The electric network frequency (ENF) as an aid to authenticating forensic digital audio recordings–an automated approach, AES 33rd International Conference, 1–10.
- ENTSO-E. (2013) European Network of Transmission System Operators for Electricity-Appendix 1 of System Operation Agreement (Vol. 1).
- Fechner, N., ve Kirchner, M. (2014) The humming hum: Background noise as a carrier of ENF artifacts in mobile device audio recordings, Proceedings - 8th International Conference on IT Security Incident Management and IT Forensics, IMF 2014, 3–13, doi: 10.1109/IMF.2014.14
- Garg, R., Varna, A. L., Hajj-Ahmad, A., ve Wu, M. (2013) “Seeing” ENF: Power-signature-based timestamp for digital multimedia via optical sensing and signal processing, IEEE Transactions on Information Forensics and Security, 8(9), 1417–1432, doi: 10.1109/TIFS.2013.2272217
- Garg, R., Varna, A., ve Wu, M. (2011) Seeing ENF: natural time stamp for digital video via optical sensing and signal processing, Proceedings of the 19th ACM International Conference on Multimedia, 23–32, doi: 10.1145/2072298.2072303
- Grigoras, C. (2005) Digital audio recording analysis–the electric network frequency criterion, International Joururnal of Speech Language and the Law, 12(1), 63–76, doi: 10.1558/sll.2005.12.1.63
- Grigoras, C. (2007) Applications of ENF criterion in forensic audio, video, computer and telecommunication analysis, Forensic Science International, 167(2-3), 136–145,doi: 10.1016/j.forsciint.2006.06.033
- Proakis, J. G., ve Manolakis, D. G. (2007) Digital Signal Processing: Principles, Algorithms, And Applications, 4/E. Pearson Education.
- Sidhu, T. S. (1999) Accurate measurement of power system frequency using a digital signal processing technique, IEEE Transactions on Instrumentation and Measurement, 48(1), 75–81, . doi: 10.1109/19.755064
- Vatansever, S. ve Dirik, A E. (2016) Forensic Analysis of Digital Audio Recordings Based on Acoustic Mains Hum, 24th Signal Processing and Communication Application Conference (SIU), 1285–88, doi: 10.1109/SIU.2016.7495982
Abstract
Electric
Network Frequency (ENF) based Forensic analysis technique of video files is one
of the most significant tools, proposed in recent years, in timestamp
verification and forgery detection of multimedia files. ENF fluctuates
continuously from its nominal value (50 Hz in Europe) depending on an increase
or decrease in total power production as against total power consumption in the
grid network. These fluctuations are the same across the entire network. Light
intensity emitted by light sources that are connected to power grid, shows
instantaneous variations, which cannot be noticed by human eye, depending on
electric network frequency. These variations in light intensity can be caught
by video cameras. With the analysis of steady content throughout the whole
frames of recorded videos, speed of light intensity variations, so power
network frequency can be estimated. By computation of the similarity between
the ENF signal estimated from video recordings and the reference ENF obtained directly
from power grid network, the information of file record time can be accessible.
In this work, it is investigated that how much the type of a light source, connected
to grid network, is influential in ENF signal quality estimated from video files captured by cameras
with CCD sensor. ENF based video record time verification performance in videos
of various lengths is analyzed in accordance with light source type.
Keywords
ENF electric network frequency video forensics video timestamp verification effect of light source
References
- Bollen, M. H., ve Gu, I. (2006) Signal Processing of Power Quality Disturbances. Wiley.
- Chai, J., Liu, F., Yuan, Z., Conners, R., ve Liu, Y. (2013) Source of ENF in Battery-Powered Digital Recordings, Audio Engineering Society Convention 135.
- Cooper, A. (2008) The electric network frequency (ENF) as an aid to authenticating forensic digital audio recordings–an automated approach, AES 33rd International Conference, 1–10.
- ENTSO-E. (2013) European Network of Transmission System Operators for Electricity-Appendix 1 of System Operation Agreement (Vol. 1).
- Fechner, N., ve Kirchner, M. (2014) The humming hum: Background noise as a carrier of ENF artifacts in mobile device audio recordings, Proceedings - 8th International Conference on IT Security Incident Management and IT Forensics, IMF 2014, 3–13, doi: 10.1109/IMF.2014.14
- Garg, R., Varna, A. L., Hajj-Ahmad, A., ve Wu, M. (2013) “Seeing” ENF: Power-signature-based timestamp for digital multimedia via optical sensing and signal processing, IEEE Transactions on Information Forensics and Security, 8(9), 1417–1432, doi: 10.1109/TIFS.2013.2272217
- Garg, R., Varna, A., ve Wu, M. (2011) Seeing ENF: natural time stamp for digital video via optical sensing and signal processing, Proceedings of the 19th ACM International Conference on Multimedia, 23–32, doi: 10.1145/2072298.2072303
- Grigoras, C. (2005) Digital audio recording analysis–the electric network frequency criterion, International Joururnal of Speech Language and the Law, 12(1), 63–76, doi: 10.1558/sll.2005.12.1.63
- Grigoras, C. (2007) Applications of ENF criterion in forensic audio, video, computer and telecommunication analysis, Forensic Science International, 167(2-3), 136–145,doi: 10.1016/j.forsciint.2006.06.033
- Proakis, J. G., ve Manolakis, D. G. (2007) Digital Signal Processing: Principles, Algorithms, And Applications, 4/E. Pearson Education.
- Sidhu, T. S. (1999) Accurate measurement of power system frequency using a digital signal processing technique, IEEE Transactions on Instrumentation and Measurement, 48(1), 75–81, . doi: 10.1109/19.755064
- Vatansever, S. ve Dirik, A E. (2016) Forensic Analysis of Digital Audio Recordings Based on Acoustic Mains Hum, 24th Signal Processing and Communication Application Conference (SIU), 1285–88, doi: 10.1109/SIU.2016.7495982
Details
| Subjects | Engineering |
|---|---|
| Journal Section | Research Articles |
| Authors | |
| Publication Date | April 10, 2017 |
| Submission Date | October 7, 2016 |
| Acceptance Date | February 20, 2017 |
| Published in Issue | Year 2017 Volume: 22 Issue: 1 |
Cite
Cited By
Ses Dosyalarının ENF Tabanlı Adli Analizine Kısa Zamanlı Fourier Dönüşümü Parametre Seçimlerinin Etkisi
Mühendislik Bilimleri ve Araştırmaları Dergisi
https://doi.org/10.46387/bjesr.1246180
The Effect of Inverse Square Law of Light on ENF in Videos Exposed by Rolling Shutter
IEEE Transactions on Information Forensics and Security
https://doi.org/10.1109/TIFS.2022.3220029
ENF Based Robust Media Time-Stamping
IEEE Signal Processing Letters
https://doi.org/10.1109/LSP.2022.3205563
Analysis of Rolling Shutter Effect on ENF-Based Video Forensics
IEEE Transactions on Information Forensics and Security
Saffet Vatansever
https://doi.org/10.1109/TIFS.2019.2895540
Announcements:
30.03.2021-Beginning with our April 2021 (26/1) issue, in accordance with the new criteria of TR-Dizin, the Declaration of Conflict of Interest and the Declaration of Author Contribution forms fulfilled and signed by all authors are required as well as the Copyright form during the initial submission of the manuscript. Furthermore two new sections, i.e. ‘Conflict of Interest’ and ‘Author Contribution’, should be added to the manuscript. Links of those forms that should be submitted with the initial manuscript can be found in our 'Author Guidelines' and 'Submission Procedure' pages. The manuscript template is also updated. For articles reviewed and accepted for publication in our 2021 and ongoing issues and for articles currently under review process, those forms should also be fulfilled, signed and uploaded to the system by authors.