拟合盲隐写分析结果的隐写组合测评方法

doi:10.3969/j.issn.1001-2400.2015.04.025

J4 ›› 2015, Vol. 42 ›› Issue (4): 153-158.doi: 10.3969/j.issn.1001-2400.2015.04.025

拟合盲隐写分析结果的隐写组合测评方法

夏冰冰;赵险峰;张弘

(中国科学院信息工程研究所信息安全国家重点实验室，北京 100093)

收稿日期:2014-03-21 出版日期:2015-08-20 发布日期:2015-10-12
通讯作者: 夏冰冰
作者简介:夏冰冰(1983-)，男，中国科学院信息工程研究所博士研究生，E-mail: xiabingbing@iie.ac.cn．
基金资助:
国家自然科学基金资助项目(61170281, 61303259, 61303254)；中国科学院战略性先导科技专项资助项目(XDA06030601)；中国科学院信息工程研究所密码基金资助项目(Y3Z0012102)

Assorted benchmarking for steganography based on blind steganalyzer accuracy fitting

XIA Bingbing;ZHAO Xianfeng;ZHANG Hong

(State Key Lab. of Information Security, Institute of Engineering, CAS, Beijing 100093, China)

Received:2014-03-21 Online:2015-08-20 Published:2015-10-12
Contact: XIA Bingbing

摘要/Abstract

摘要：

KL距离(Kullback-Leibler Divergence)能够衡量原文与隐文特征集的可区分性，但其计算复杂度过高，不适合作为隐写测评指标．现有测评方法通过某种便于计算的统计量，从不同角度衡量原文与隐文特征集的距离，其测评效果有限．为了解决这一问题，提出了拟合盲隐写分析结果的隐写隐蔽性组合测评方法，基于平均单维互信息和最大平均偏差这两种存在一定互补性的基础隐写测评指标构造新的测评指标，从而获得对隐写隐蔽性更加全面客观的评价．

关键词: 隐写测评, 互信息, 最大平均偏差, 回归分析

Abstract:

KL divergence gives a precise estimation of the difference between cover and stego mediums, but the high computational complexity makes it impropriate for steganography benchmarking. The existing benchmarking methods use other statistics to evaluate the divergence between cover and stego features, but the performance is relatively poor. To solve this problem, we propose an assorted benchmarking for steganography based on blind steganalyzer accuracy fitting. The two complementary basic statistics, i.e., the mean value of single dimensional mutual information and the maximum mean discrepancy, are combined to obtain a better estimate of the divergence between cover and stego features.

Key words: steganography benchmarking, mutual information, maximum mean discrepancy, regression analysis

夏冰冰;赵险峰;张弘 . 拟合盲隐写分析结果的隐写组合测评方法[J]. J4, 2015, 42(4): 153-158.

XIA Bingbing;ZHAO Xianfeng;ZHANG Hong. Assorted benchmarking for steganography based on blind steganalyzer accuracy fitting[J]. J4, 2015, 42(4): 153-158.

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拟合盲隐写分析结果的隐写组合测评方法

Assorted benchmarking for steganography based on blind steganalyzer accuracy fitting

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