Steganalysis based on transfer learning

Deng-pan YE; Fang-fang MA; Yuan MEI

doi:10.11959/j.issn.2096-109x.2017.00116

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Steganalysis based on transfer learning

Academic paper | 更新时间：2024-06-03

- Steganalysis based on transfer learning
- Journal of network and information security Vol. 3, Issue 1, Pages: 23-30(2017)
- 作者机构：
- 作者简介：
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- DOI：10.11959/j.issn.2096-109x.2017.00116
  CLC： TP309.7
- Online First：2017-01，
  
  Published：15 January 2017
- 稿件说明：
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Deng-pan YE, Fang-fang MA, Yuan MEI. Steganalysis based on transfer learning[J]. Journal of network and information security, 2017, 3(1): 23-30.
DOI：

Deng-pan YE, Fang-fang MA, Yuan MEI. Steganalysis based on transfer learning[J]. Journal of network and information security, 2017, 3(1): 23-30. DOI： 10.11959/j.issn.2096-109x.2017.00116.

摘要

在实际应用环境下，训练集和测试集往往存在分布偏差，导致隐写分析检测效果不理想。迁移学习方法旨在从一个领域学习到的知识，来帮助完成新领域中的学习任务，不要求领域间的同分布假设。概述了当前隐写分析失配问题的研究现状，分析了引起隐写分析失配的因素，在TrAdaBoost迁移算法的基础上提出了一种基于迁移学习的隐写分析算法，改善了隐写检测过程中出现的失配问题，并通过实验验证了算法的有效性。

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.

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references

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