基于设备本底噪声频谱特征的手机来源识别

doi:10.11959/j.issn.1000-0801.2017019

Abstract

Abstract:

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.

Key words: multimedia forensics, cell-phone origin identification, self-noise, spectral feature

CLC Number:

TP391

Anshan PEI,Rangding WANG,Diqun YAN. Cell-phone origin identification based on spectral features of device self-noise[J]. Telecommunications Science, 2017, 33(1): 85-94.

Figures/Tables 10

References 19

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标签												预测标签
标签	H₁	H₂	H₃	W₁	W₂	W₃	A₁	A₂	A₃	A₄	A₅	Z₁	Z₂	Z₃	M₁	M₂	M₃	M₄	O₁	O₂	O₃	S₁	S₂	S₃
H₁	100%	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
H₂	2.5%	97.5%	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
H₃	0	0	100%	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
W₁	0	0	0	100%	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
W₂	0	0	0	2.5%	97.5%	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
W₃	0	0	0	0	0	100%	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
A₁	0	0	0	0	0	0	97.5%	0	0	1.7%	0	0	0.8%	0	0	0	0	0	0	0	0	0	0	0
A₂	0	0	0	0	0	0	0	100%	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
A₃	0	0	0	0	0	0	0	0	98.3%	1.7%	0	0	0	0	0	0	0	0	0	0	0	0	0	0
A₄	0	0	0	0	0	0	2.5%	0	5.8%	91.7%	0	0	0	0	0	0	0	0	0	0	0	0	0	0
A₅	0	0	0	0	0	0	0	0	0	0	100%	0	0	0	0	0	0	0	0	0	0	0	0	0
Z₁	0	0	0	0	0	0	0	0	0	0	0	100%	0	0	0	0	0	0	0	0	0	0	0	0
Z₂	0	0	0	0	0	0	0	0	0	0	0	0	100%	0	0	0	0	0	0	0	0	0	0	0
Z₃	0	0	0	0	0	0	0	0	0	0	0	0	0	100%	0	0	0	0	0	0	0	0	0	0
M₁	0	0	0	0	0	0	0	0	0	0	0	0	0	0	100%	0	0	0	0	0	0	0	0	0
M₂	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	100%	0	0	0	0	0	0	0	0
M₃	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	100%	0	0	0	0	0	0	0
M₄	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	99.2%	0.8%	0	0	0	0	0
O₁	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	100%	0	0	0	0	0
O₂	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	100%	0	0	0	0
O₃	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	100%	0	0	0
S₁	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	100%	0	0
S₂	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	100%	0
S₃	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	100%

标签												预测标签
标签	H₁	H₂	H₃	W₁	W₂	W₃	A₁	A₂	A₃	A₄	A₅	Z₁	Z₂	Z₃	M₁	M₂	M₃	M₄	O₁	O₂	O₃	S₁	S₂	S₃
H₁	97%	1%	0	0	2%	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
H₂	2%	98%	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
H₃	0	0	100%	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
W₁	0	0	0	97%	3%	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
W₂	0	0	0	0	100%	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
W₃	0	0	0	0	1%	99%	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
A₁	0	0	0	0	0	0	99%	0	0	1%	0	0	0	0	0	0	0	0	0	0	0	0	0	0
A₂	0	0	0	0	2%	0	0	97%	1%	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
A₃	0	0	0	0	0	0	1%	3%	94%	2%	0	0	0	0	0	0	0	0	0	0	0	0	0	0
A₄	0	0	0	0	0	0	5%	0	0	95%	0	0	0	0	0	0	0	0	0	0	0	0	0	0
A₅	0	0	0	0	0	0	1%	0	0	0	97%	0	2%	0	0	0	0	0	0	0	0	0	0	0
Z₁	0	0	0	0	1%	0	0	0	0	0	0	98%	0	0	0	0	0	0	0	1%	0	0	0	0
Z₂	0	0	0	0	0	0	0	0	0	0	0	0	100%	0	0	0	0	0	0	0	0	0	0	0
Z₃	0	0	0	0	0	0	0	0	0	0	0	1%	2%	97%	0	0	0	0	0	0	0	0	0	0
M₁	0	0	0	0	0	0	0	0	0	0	0	0	1%	0	99%	0	0	0	0	0	0	0	0	0
M₂	0	0	0	0	0	0	0	0	1%	0	0	0	0	0	0	99%	0	0	0	0	0	0	0	0
M₃	0	0	0	0	1%	0	0	0	0	0	0	0	0	0	0	0	99%	0	0	0	0	0	0	0
M₄	0	0	0	0	1%	0	0	0	0	0	0	0	0	0	0	0	0	99%	0	0	0	0	0	0
O₁	0	0	0	0	0	0	0	0	0	0	0	0	1%	0	0	0	0	0	99%	0	0	0	0	0
O₂	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	100%	0	0	0	0
O₃	0	0	0	0	0	0	0	0	0	0	0	0	2%	0	0	0	0	0	0	0	98%	0	0	0
S₁	0	0	0	0	0	0	0	0	0	0	0	0	2%	0	0	0	0	0	1%	0	0	97%	0	0
S₂	0	0	0	0	3%	0	0	0	0	0	0	0	1%	0	0	0	0	0	0	0	0	0	96%	0
S₃	0	0	0	0	0	0	0	0	0	0	0	0	1%	0	0	0	0	0	0	0	0	0	0	99%

标签												预测标签
标签	H₁	H₂	H₃	W₁	W₂	W₃	A₁	A₂	A₃	A₄	A₅	Z₁	Z₂	Z₃	M₁	M₂	M₃	M₄	O₁	O₂	O₃	S₁	S₂	S₃
H₁	50%	49.2%	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0.8%	0	0	0	0	0	0
H₂	20.8%	79.2%	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
H₃	2.5%	0	96.7%	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0.8%	0	0	0	0	0
W₁	0	0	0	96.7%	1.7%	0.8%	0	0	0	0	0	0	0	0	0	0.8%	0	0	0	0	0	0	0	0
W₂	0	0	0	0	100%	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
W₃	0	0	0	4.2%	0	94.2%	0	0	0	0	0	0	0.8%	0	0	0.8%	0	0	0	0	0	0	0	0
A₁	0	0	0	0	0	0	62.5%	0.8%	5%	31.7%	0	0	0	0	0	0	0	0	0	0	0	0	0	0
A₂	0	0	0	0	0	0	0	100%	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
A₃	0	0	0	0	0	0	15%	1.7%	75.8%	7.5%	0	0	0	0	0	0	0	0	0	0	0	0	0	0
A₄	0	0	0	0	0	0	21.7%	0.8%	10.8%	66.7%	0	0	0	0	0	0	0	0	0	0	0	0	0	0
A₅	0	0	0	0	0	0	0	0	0	0	100%	0	0	0	0	0	0	0	0	0	0	0	0	0
Z₁	0	0	0	0	0	0	0	0	0	0	0	85%	0	15%	0	0	0	0	0	0	0	0	0	0
Z₂	0	0	0.8%	1.7%	0	0	0	0	0	0	0	0	97.5%	0	0	0	0	0	0	0	0	0	0	0
Z₃	2.5%	0	0	0	0	0	0	0	0	0	0	0	0	96.7%	0	0	0	0	0	0.8%	0	0	0	0
M₁	0	0	0	0	0	0	0	0	0	0	0	0	0	0	99.2%	0	0	0	0.8%	0	0	0	0	0
M₂	0	0	0	2.5%	0	0.8%	0	0	0	0	0	0	0	0	0	96.7%	0	0	0	0	0	0	0	0
M₃	0	0	1.7%	0	0	0	0	0	0	0	0	0	0	0	0	0	97.5%	0	0	0	0.8%	0	0	0
M₄	10%	1.7%	5.8%	0	0	0.8%	0	0	0	0	0	0	0.8%	4.2%	0	0	0	75%	0	0	0	1.7%	0	0
O₁	0	0	0	0	0	0	0	0	0	0	0	0	2.5%	0.8%	0.8%	0	0	0.8%	87.5%	5.8%	0	0	0	1.7%
O₂	0	0	0	0	0	0	0	0	0	0	0	0	0	0.8%	0	0	0	0	0	93.3%	0	0	0	5.8%
O₃	0	0	2.5%	0	0	0	0	0	0	0	0.8%	0	0	0	0	0	4.2%	0	0	0	92.5%	0	0	0
S₁	5%	0	4.2%	0	0	0	0	0	0	0	0	0	0	0	0	0	0	5%	4.2%	0	0	80.8%	0	0.8%
S₂	0	0	0%	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	100%	0
S₃	0.8%	0	4.2%	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0.8%	0	0	0	94.2%

Cell-phone origin identification based on spectral features of device self-noise

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