基于图像来源分类的最小化虚警隐写分析模型

doi:10.11959/j.issn.1000-436x.2016282

Abstract

Abstract:

In the real world, reducing false positive rates in the case of cover source mismatch (CSM) was a big challenge for steganalysis. A novel model was proposed to solve the problem. The proposed method determines the im-age-acquiring source firstly by a source detector and then detecting the steg images in each source with a steganalyzer trained for this source. The false positive rate was reduced by solving a parameter model. The experimental results show that this novel method can reach lower false positive rates for larger true positive rates.

Key words: false positive, mismatch, steganalysis, minimum false positive model

Pei-tao YANG,Wei-ming ZHANG,Neng-hai YU. Reducing false positives of steganalysis via classification of image-acquiring sources[J]. Journal on Communications, 2016, 37(12): 165-170.

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References 20

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图像来源	图像数量/张
iP4	7 136
iP5	10 000
NK7	8 420
NK3	10 000
ST	6 000
合计	41 556

			测试集

训练集	iP4	iP5	NK7	NK3	ST
iP4	0.322 8	0.346 2	0.488 3	0.401 2	0.481 2
iP5	0.444 7	0.265 2	0.486 1	0.389 6	0.461 6
NK7	0.439 5	0.426 2	0.206 7	0.430 5	0.486 2
NK3	0.439 0	0.378 4	0.420 3	0.272 7	0.477 4
ST	0.490 8	0.475 5	0.492 7	0.440 8	0.387 7

			测试集

训练集	iP4	iP5	NK7	NK3	ST
iP4	0.118 5	0.159 1	0.244 0	0.188 8	0.472 5
iP5	0.417 7	0.091 2	0.274 1	0.287 1	0.378 2
NK7	0.285 3	0.245 1	0.025 1	0.204 9	0.414 1
NK3	0.352 9	0.222 7	0.237 4	0.069 1	0.425 6
ST	0.480 0	0.396 4	0.451 1	0.368 7	0.212 7

Reducing false positives of steganalysis via classification of image-acquiring sources

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