基于联合质心熵的网络流水印自适应检测方案

doi:10.3969/j.issn.0255-8297.2018.02.016

Journal of Applied Sciences ›› 2018, Vol. 36 ›› Issue (2): 383-392.doi: 10.3969/j.issn.0255-8297.2018.02.016

• Special Issue: Information Security of Multimedia Contents • Previous Articles Next Articles

Adaptive Network Flow Watermarking Detection Scheme Based on Joint Centroid Entropy

SHI Jin¹, LI Qian-kun², LIU Wei-wei¹, LIU Guang-jie¹, DAI Yue-wei³

1. School of Automation, Nanjing University of Science and Technology, Nanjing 210094, China;
2. Intelligence Division, The 10 th Research Institute of China Electronic Technology Group Corporation, Chengdu 610036, China;
3. School of Electronics and Information, Jiangsu University of Science and Technology, Zhenjiang 212003, Jiangsu Province, China

Received:2018-01-31 Online:2018-03-31 Published:2018-03-31

Abstract

Abstract:

Considering the differences of watermarking in various types of complex network trafc, a new pre-grouping mechanism based on total packets number, average packets interval and bytes symmetry is designed. On this basis, an adaptive network flow watermarking detection scheme based on joint centroid entropy is proposed with the exploitation of the statistic variation of network trafc which is caused by interval-based flow watermarking. Experimental results on different types of trafc in anonymous communication system Tor show that the proposed method can achieve higher detection accuracy for random multi-key interval centroid based watermarking.

Key words: joint centroid entropy, anonymous communication, network flow watermarking, pre-grouping

CLC Number:

TP393

SHI Jin, LI Qian-kun, LIU Wei-wei, LIU Guang-jie, DAI Yue-wei. Adaptive Network Flow Watermarking Detection Scheme Based on Joint Centroid Entropy[J]. Journal of Applied Sciences, 2018, 36(2): 383-392.

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Adaptive Network Flow Watermarking Detection Scheme Based on Joint Centroid Entropy

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