Cell-phone origin identification based on spectral features of device self-noise
With the widespread availability of cell-phone recording devices and the availability of various powerful and easy-to-use digital media editing software,source cell-phone identification has become a hot topic in multimedia forensics.A novel cell-phone identification method was proposed based on the...
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| Format: | Article |
| Language: | zho |
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Beijing Xintong Media Co., Ltd
2017-01-01
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| Series: | Dianxin kexue |
| Subjects: | |
| Online Access: | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2017019/ |
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| _version_ | 1841530090960191488 |
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| author | Anshan PEI Rangding WANG Diqun YAN |
| author_facet | Anshan PEI Rangding WANG Diqun YAN |
| author_sort | Anshan PEI |
| collection | DOAJ |
| description | With the widespread availability of cell-phone recording devices and the availability of various powerful and easy-to-use digital media editing software,source cell-phone identification has become a hot topic in multimedia forensics.A novel cell-phone identification method was proposed based on the recorded speech.Firstly,device self-noise (DSN) was considered as the fingerprint of the cell-phone and estimated from the silent segments of the speech.Then,the mean of the noise's spectrum was extracted as the identification.Principal components analysis (PCA) was applied to reduce the feature dimension.Support vector machine (SVM) was adopted as the classifier to determine the source of the detecting speech.Twenty-four popular models of the cell-phones were evaluated in the experiment.The experimental results show that the average identification accuracy and recall of the method can reach up to 99.24% and demonstrate that the self-noise feature has more superior performance than the MFCC feature. |
| format | Article |
| id | doaj-art-d6dc9ff9a22f43c1a4793e357ae31112 |
| institution | Kabale University |
| issn | 1000-0801 |
| language | zho |
| publishDate | 2017-01-01 |
| publisher | Beijing Xintong Media Co., Ltd |
| record_format | Article |
| series | Dianxin kexue |
| spelling | doaj-art-d6dc9ff9a22f43c1a4793e357ae311122025-01-15T03:13:31ZzhoBeijing Xintong Media Co., LtdDianxin kexue1000-08012017-01-0133859459604051Cell-phone origin identification based on spectral features of device self-noiseAnshan PEIRangding WANGDiqun YANWith the widespread availability of cell-phone recording devices and the availability of various powerful and easy-to-use digital media editing software,source cell-phone identification has become a hot topic in multimedia forensics.A novel cell-phone identification method was proposed based on the recorded speech.Firstly,device self-noise (DSN) was considered as the fingerprint of the cell-phone and estimated from the silent segments of the speech.Then,the mean of the noise's spectrum was extracted as the identification.Principal components analysis (PCA) was applied to reduce the feature dimension.Support vector machine (SVM) was adopted as the classifier to determine the source of the detecting speech.Twenty-four popular models of the cell-phones were evaluated in the experiment.The experimental results show that the average identification accuracy and recall of the method can reach up to 99.24% and demonstrate that the self-noise feature has more superior performance than the MFCC feature.http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2017019/multimedia forensicscell-phone origin identificationself-noisespectral feature |
| spellingShingle | Anshan PEI Rangding WANG Diqun YAN Cell-phone origin identification based on spectral features of device self-noise Dianxin kexue multimedia forensics cell-phone origin identification self-noise spectral feature |
| title | Cell-phone origin identification based on spectral features of device self-noise |
| title_full | Cell-phone origin identification based on spectral features of device self-noise |
| title_fullStr | Cell-phone origin identification based on spectral features of device self-noise |
| title_full_unstemmed | Cell-phone origin identification based on spectral features of device self-noise |
| title_short | Cell-phone origin identification based on spectral features of device self-noise |
| title_sort | cell phone origin identification based on spectral features of device self noise |
| topic | multimedia forensics cell-phone origin identification self-noise spectral feature |
| url | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2017019/ |
| work_keys_str_mv | AT anshanpei cellphoneoriginidentificationbasedonspectralfeaturesofdeviceselfnoise AT rangdingwang cellphoneoriginidentificationbasedonspectralfeaturesofdeviceselfnoise AT diqunyan cellphoneoriginidentificationbasedonspectralfeaturesofdeviceselfnoise |