Online universal steganalysis system based on multiple pre-trained model

Ya-fei YUAN; Wei LU; Bing-wen FENG; Jian WENG

doi:10.11959/j.issn.2096-109x.2017.00164

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Online universal steganalysis system based on multiple pre-trained model

Papers | 更新时间：2024-06-03

- Online universal steganalysis system based on multiple pre-trained model
- Chinese Journal of Network and Information Security Vol. 3, Issue 5, Pages: 32-37(2017)
- 作者机构：
  
  1. 中山大学数据科学与计算机学院，广东广州 510006
  2. 暨南大学信息科学技术学院，广东广州 510632
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.2096-109x.2017.00164
  CLC： TP393
- Online First：2017-05，
  
  Published：15 May 2017
- 稿件说明：
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Ya-fei YUAN, Wei LU, Bing-wen FENG, et al. Online universal steganalysis system based on multiple pre-trained model[J]. Chinese Journal of Network and Information Security, 2017, 3(5): 32-37.
DOI：

Ya-fei YUAN, Wei LU, Bing-wen FENG, et al. Online universal steganalysis system based on multiple pre-trained model[J]. Chinese Journal of Network and Information Security, 2017, 3(5): 32-37. DOI： 10.11959/j.issn.2096-109x.2017.00164.

摘要

在实际应用中，针对未知隐写算法的盲检测难度非常大，结合实际应用设计实现了一个在线盲检测系统。在SRM算法的基础上，简化特征提取算法，提高特征可用性和提取速率；使用多个预训练检测模型，并采用加权投票策略判定检测结果；设计实现一种3层系统架构，分布式后台更加灵活高效；为了进一步满足实际应用要求，引入多线程技术，加快检测速率。实验表明，单张图片的平均检测时间可达0.97 s，并且对多种未知隐写算法均具有良好的检测结果。

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.

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references

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