吉林大学学报(工学版) ›› 2016, Vol. 46 ›› Issue (2): 658-662.doi: 10.13229/j.cnki.jdxbgxb201602048

• Orginal Article • Previous Articles     Next Articles

Croup traitor tracking in the multimedia group fingerprinting system

ZHAO Yong, XIA Zheng-min   

  1. School of Electronic Information and Electrical Engineering, Shanghai Jiaotong University, Shanghai 200240, China
  • Received:2014-06-29 Online:2016-02-20 Published:2016-02-20

RICH HTML

0   

PDF (PC)

274

Abstract: The composite orthogonal, composite coded, Discrete Cosine Transform (DCT), and Discrete Wavelet Transform (DWT) group fingerprinting schemes are constructed. Based on these schemes, the group traitor tracking algorithms (e.g. maximum correlation detector) are implemented. Experiments are carried out to compare the performance of these constructed group fingerprinting schemes. Results show that in all cases the group fingerprinting schemes can perform group detection effectively. The composite coded group fingerprinting scheme performs the best in noisy environment and after JPEG compression. The DWT scheme performs the best under group colluding attacks from different groups and the signal group.

Key words: information processing techniques, group fingerprint, group collusion, group tracing, performance comparison

CLC Number: 

  • TP391
[1] Chor B, Fiat A, Naor M, et al. Tracing traitors[J]. IEEE Transactions on Information Theory, 2000, 46(3): 893-910.
[2] Kuribayashi M.A simple tracing algorithm for binary fingerprinting code under averaging attack[C]//The 1st ACM Workshop on Information Hiding and Multimedia Security,Montpellier,France,2013:3-12.
[3] Marcel S, Waldemar B, Martin S. Fast and adaptive tracing strategies for 3-secure fingerprint watermarking codes[C]//ACM Workshop on Digital Rights Management, Chicago, Illinois, USA, 2011: 41-50.
[4] Zhao Yong, Zhang Ai-xin, Lu Song-nian. Group fingerprinting communication protocols for digital wholesale and retail in E-commerce[C]//The 2rd International Conference on Informatics and Applications, Lodz, Poland, 2013: 143-146.
[5] Mintzer F, Braudaway G W. If one watermark is good, are more better?[C]//Proceedings of the International Conference on Acoustics, Speech and Signal Processing, Phoenix, Arizona, USA, 1999: 2067-2070.
[6] Chu S C, Jain L C, Huang H C, et al. The triple-watermarking algorithm with multiple description coding over lossy communication networks[C]//The 3rd International Conference on Ubiquitous Information Management and Communication, Suwon, Korea, 2009: 317-326.
[7] Raval M S, Rege P P. Discrete wavelet transform based multiple watermarking schemes[C]//Conference on Convergent Technologies for the Asia-Pacific region, Taj Residency, Bangalore, 2003: 935-938.
[8] Wang Z, Wu M, Trappe W, et al. Group-oriented fingerprinting for multimedia forensics[J]. EURASIP Journal on Applied Signal Processing, 2004, 14: 2142-2162.
[9] Tirkel A Z, Hall T E, Osborne C F. Collusion resistant fingerprinting of digital audio[C]//The 4th International Conference on Security of Information and Networks, Sydney, Australia, 2011: 5-12.
[10] Wang Z J, Wu M, Zhao H V, et al. Anti-collusion forensics of multimedia fingerprinting using orthogonal modulation[J]. IEEE Transactions on Image Processing, 2005, 14(6): 804-821.
[11] He S, Wu M. Adaptive detection for group-based multimedia fingerprinting[J]. IEEE Signal Processing Letters, 2007, 14(12): 964-967.
[12] Jin H X, Lotspiech J, Nelson M, et al. Adaptive traitor tracing for large anonymous attack[C]//ACM Workshop on Digital Rights Management, Alexandria, Virginia, USA, 2008: 1-8.
[13] Zhao Yong, Zhang Ai-xin, Lu song-nian. DCT fingerprint classifier based group fingerprint[C]//International Conference on Audio, Language, and Image Processing, Shanghai, China, 2014:292-295.
[14] Zhao Yong, Zhang Ai-xin, Lu Song-nian. The DWT group fingerprinting scheme[C]//IEEE International Conference on Dependable, Autonomic and Secure Computing, Dalian, China, 2014:81-84.
[1] LIU Fu,ZONG Yu-xuan,KANG Bing,ZHANG Yi-meng,LIN Cai-xia,ZHAO Hong-wei. Dorsal hand vein recognition system based on optimized texture features [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1844-1850.
[2] LIU En-ze,WU Wen-fu. Agricultural surface multiple feature decision fusion disease judgment algorithm based on machine vision [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1873-1878.
[3] XU Yan,SUN Mei-shuang. Enhancing underwater image based on convolutional neural networks [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1895-1903.
[4] HUANG Yong,YANG De-yun,QIAO Sai,MU Zhen-guo. Target detecting with conjugate CFAR in VHR SAR image [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1904-1909.
[5] LU Zhi-jun,ZHONG Chao,WU Jing-yu. Small feature segmentation method for Spaceborne SAR images [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1925-1930.
[6] LIU Zhong-min,WANG Yang,LI Zhan-ming,HU Wen-jin. Image segmentation algorithm based on SLIC and fast nearest neighbor region merging [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1931-1937.
[7] OUYANG Dan-tong, FAN Qi. Clause-level context-aware open information extraction [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(5): 1563-1570.
[8] LIU Fu, LAN Xu-teng, HOU Tao, KANG Bing, LIU Yun, LIN Cai-xia. Metagenomic clustering method based on k-mer frequency optimization [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(5): 1593-1599.
[9] LIU Yuan-ning, LIU Shuai, ZHU Xiao-dong, CHEN Yi-hao, ZHENG Shao-ge, SHEN Chun-zhuang. LOG operator and adaptive optimization Gabor filtering for iris recognition [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(5): 1606-1613.
[10] LIU Zhe, XU Tao, SONG Yu-qing, XU Chun-yan. Image fusion technology based on NSCT and robust principal component analysis model with similar information [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(5): 1614-1620.
[11] CHE Xiang-jiu, WANG Li, GUO Xiao-xin. Improved boundary detection based on multi-scale cues fusion [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(5): 1621-1628.
[12] CAO Jie, SU Zhe, LI Xiao-xu. Image annotation method based on Corr-LDA model [J]. 吉林大学学报(工学版), 2018, 48(4): 1237-1243.
[13] HOU Yong-hong, WANG Li-wei, XING Jia-ming. HTTP-based dynamic adaptive streaming video transmission algorithm [J]. 吉林大学学报(工学版), 2018, 48(4): 1244-1253.
[14] LI Zhi-hui, HU Yong-li, ZHAO Yong-hua, MA Jia-lei, LI Hai-tao, ZHONG Tao, YANG Shao-hui. Locating moving pedestrian from running vehicle [J]. 吉林大学学报(工学版), 2018, 48(3): 694-703.
[15] YANG Dong-sheng, ZHANG Zhan, LIAN Meng-jia, WANG Li-na. Matching binary feature search algorithm of bitmap locality sensitive hashing [J]. 吉林大学学报(工学版), 2018, 48(3): 893-902.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
Copyright © Journal of Jilin University(Engineering and Technology Edition), All Rights Reserved.
Tel: +86-431-85095297　Fax: +86-431-85094074　E-mail: xbgxb@jlu.edu.cn
Powered by Beijing Magtech Co. Ltd