Chinese Journal of Network and Information Security ›› 2017, Vol. 3 ›› Issue (1): 23-30.doi: 10.11959/j.issn.2096-109x.2017.00116

• Academic paper • Previous Articles     Next Articles

Steganalysis based on transfer learning

Deng-pan YE,Fang-fang MA(),Yuan MEI   

  1. Computer School, Wuhan University, Wuhan 430072,China
  • Revised:2016-10-09 Online:2017-01-15 Published:2020-03-20
  • Supported by:
    The National Natural Science Foundation of China(61272453);Major Scientific and Technological InnovationProject of Hubei Province(2015AAA013);NSFC-General Technology Foundation Research United Fund(U1236204)

Abstract:

In practice, when the training set and testing set are mismatched, performance of steganalysis can not be guaranteed. The transfer learning aims at using the knowledge learned from one domain to help complete the learn-ing task in the new domain, and does not require the same distribution assumption. A more comprehensive review of mismatched steganography research status was made and the mismatch factors were analyzed. Methods on in-stance-based transfer learning were presented to solve the test mismatch problem during the steganography detections.

Key words: steganography, transfer learning, based on instance

CLC Number: 

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