Reducing false positives of steganalysis via classification of image-acquiring sources - Pei-tao YANG; Wei-ming ZHANG; Neng-hai YU (Tongxin xuebao)
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.