Chinese Journal of Network and Information Security ›› 2017, Vol. 3 ›› Issue (5): 32-37.doi: 10.11959/j.issn.2096-109x.2017.00164

• Papers • Previous Articles     Next Articles

Online universal steganalysis system based on multiple pre-trained model

Ya-fei YUAN1,Wei LU1,Bing-wen FENG2,Jian WENG2   

  1. 1 School of Data and Computer Science,Sun Yat-sen University,Guangzhou 510006,China
    2 College of Information Science and Technology,Jinan University,Guangzhou 510632,China
  • Revised:2017-03-26 Online:2017-05-01 Published:2017-05-13
  • Supported by:
    The Special Funds for Science and Technology Development of Guangdong Province(2016KZ010103);The Natural Science Foundation of Guangdong Province(2016A030313350);The Fundamental Research Funds for the Central Universities(16lgjc83);The Scientific and Technological Achievements Transformation Plan of Sun Yat-sen University

Abstract:

In reality,universal blind steganalysis is still a sensitive issue.A universal online steganalysis system that could be used in practical application was proposed.With reducing the dimensions of SRM,it could improve availability and speed up feature extraction.Some effective pre-trained models and weighted voting strategy were used in this system with a B/S architecture,involving a higher speed.In addition,multithread technology was introduced.Experimental results demonstrate that high detection accuracy can be obtained and about 0.97 seconds for single detection with the system.

Key words: digital image steganography, steganalysis, multi-model, weighted voting, online detection

CLC Number: 

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