期刊文献+

基于时域统计特征的音频内容取证新算法 被引量:2

A Novel Audio Content Forensics Scheme Based on Time Domain Statistical Characteristic
下载PDF
导出
摘要 针对现有音频内容取证算法采用二值图像作为辨识水印所带来的安全隐患,以及基于音频内容或特征生成的辨识水印稳定性不高,易被常规信号处理操作淹没的问题,提出了一种新的基于时域统计特征的音频内容取证算法。通过对音频信号时域统计平均值进行非均匀量化生成辨识水印。理论和实验结果表明通过该方法生成的辨识水印能够抵抗常规信号处理操作,稳定性高。生成的辨识水印存储于认证中心,组建辨识水印库。对音频内容进行取证时,将由该音频生成的辨识水印与从水印库中提取的对应辨识水印进行比对,即可对待取证音频的真实性、完整性进行鉴定。该取证方法操作简便,对不同类型音频均能实现篡改定位,对常规音频信号处理操作的鲁棒性高,有效扩大了基于内容音频取证算法的应用范围。 Many previous audio content forensics schemes adopt binary image as identifying watermark, which introduces security holes to forensics systems. On the other hand, partial content-based or feature-based identifying watermarks have feeblish stability and may be damaged under various signal processing operations. To overcome these problems, a novel audio content forensics scheme based on time domain sta-tistical characteristic is proposed in this paper. The statistical average value of continuous audio samples is used to generate identifying watermark by non-uniform quantization. Theoretical analysis and experimental results show that the generated identifying watermark is robust against various signal processing operations. Various identifying watermarks generated from different audio signals are stored at CA ( Center of Authenti-cation). When authenticating the veracity and integrity of audio content, firstly identifying watemark is generated from the to be detected audio, then corresponding identifying watermark is extracted from data-base of CA, finally the two identifying watermarks for audio content forensics are compared. The proposed forensics scheme has lower computation complexity, and the ability of tamper localization and tolerance a-gainst common signal processing operations are excellent. It greatly expands the applicability of content- based audio forensics scheme.
作者 谢玲 范明泉
出处 《电讯技术》 北大核心 2013年第11期1476-1481,共6页 Telecommunication Engineering
关键词 音频内容取证 辨识水印 篡改定位 非均匀量化 时域统计特征 混沌系统 audio content forensics identifying watermark tamper localization non-uniform quantiza-tion time domain statistical characteristic chaotic system
  • 相关文献

参考文献11

  • 1Nishimura R. Audio Watermarking Using Spatial Maskingand Ambisonics[ J]. IEEE Transactions on Audio,Speech,and Language Processing, 2012 , 20(9) :2461-2469.
  • 2Xiang Yong, Natgunanathan I, Peng Dezhong,et al. ADual-channel Time-spread Echo Method for Audio Wa-termarking[ J]. IEEE Transactions on Information Foren-sics and Security, 2012,7(2) :383-392.
  • 3Khan M K, Xie Ling, Zhang Jiashu. Chaos and NDFT-based Spread Spectrum Concealing of Fingerprint-biomet-ric Data into Audio Signals [ J ]. Digital Signal Process-ing, 2010,20(1) :179-190.
  • 4王向阳,祁薇.用于版权保护与内容认证的半脆弱音频水印算法[J].自动化学报,2007,33(9):936-940. 被引量:21
  • 5Chen Ning, Zhu Jie. A Multipurpose Audio Watermark-ing Scheme for Copyright Protection and Content Authen-tication [C ] //Proceedings of 2008 IEEE InternationalConference on Multimedia and Expo. Hannover : IEEE,2008:221-224.
  • 6范明泉,王宏霞.基于音频内容的混合域脆弱水印算法[J].铁道学报,2010,32(1):118-122. 被引量:14
  • 7Chen Fan, He Hongjie, Wang Hongxia. A Fragile Water-marking Scheme for Audio Detection and Recovery [ C ] //Proceedings of 2008 IEEE International Conference on Im-age and Signal Processing. Sanya:IEEE,2008 :135-138.
  • 8Gulbis M,Muller E,Steinebach M. Content-based Authen-tication Watermarking with Improved Audio Content FeatureExtraction [ C ]//Proceedings of 2008 IEEE InternationalConference on Intelligent Information Hiding and MultimediaSignal Processing. Harbin : IEEE, 2008 :620-623.
  • 9王宏霞,范明泉.基于质心的混合域半脆弱音频水印算法[J].中国科学:信息科学,2010,40(2):313-326. 被引量:12
  • 10Xiang Shijun, Huang Jiwu. Time - scale Invariant AudioWatermarking Based on the Statistical Features in TimeDomain [ C ]//Proceedings of 2006 International Confer-ence on Information Hiding. Virginia:Springer,2006:l-16.

二级参考文献28

  • 1李伟,袁一群,李晓强,薛向阳,陆佩忠.数字音频水印技术综述[J].通信学报,2005,26(2):100-111. 被引量:73
  • 2全笑梅,张鸿宾.用于篡改检测及认证的脆弱音频水印算法[J].电子与信息学报,2005,27(8):1187-1192. 被引量:14
  • 3LI Wei, XUE Xiang-yang, LU Pei-ahong. Localized audio watermarking technique robust against time-scale modification[J].IEEE Transactions on Multimedia, 2006, 8(1): 60-69.
  • 4XIANG Sbi-jun, HUANG Ji-wu. Histogram based audio watermarking against time-scale modification and cropping attacks[J]. IEEIE Transactions on Multimedia, 2007, 9 (7) : 1357-1372.
  • 5WANG Xiang-yang, ZHAO Hong. A novel synchronization invariant audio watermarking scheme based on DWT and DCT[J].IEEE Transactions on Signal Processing, 2006, 54(12): 4835-4840.
  • 6Kundur D, Hatzinakos D. Digital watermarking for telltale tamper proofing and authentication[J]//Proeeedings of the IEEE, 1999, 87(7) : 1167-1180.
  • 7王向阳,祁薇.用于版权保护与内容认证的半脆弱音频水印算法[J].自动化学报,2007,33(9):936-940. 被引量:21
  • 8Malik H,Ansari R,Khokhar A.Robust audio watermarking using frequency-selective spread spectrum. IET Inform Secur . 2008
  • 9Chen O T-C,Liu C-H.Content-dependent watermarking scheme in compressed speech with identifying manner and location of attacks. IEEE Trans Audi Speech Lang P . 2007
  • 10Chen F,He H J,Wang H X.A fragile watermarking scheme for audio detection and recovery. Proceedings of International Congress on Image and Signal Processing . 2008

共引文献37

同被引文献47

  • 1高阳,黄征,徐彻,施少培,杨旭.基于高阶频谱分析的音频篡改鉴定[J].信息安全与通信保密,2008,30(2):94-96. 被引量:8
  • 2Maher R. Audio forensic examination[J]. Signal Processing Magazine, IEEE,2009, 26(2) :84-94.
  • 3Petrovic R. Digital watermarks for audio integrity verifieation[C]//7th International Conference on Telecommunications in Modern Satellite, Cable and Broadcasting Services, Serbia and Montenegro. Yugoslavia: IEEE Computer Society Press, 2005:215-220.
  • 4Kirbiz S, Lemma A N,Celik M U, et al. Decode-time forensic watermarking of AAC bitstreams[J]. IEEE Transactions on In-formation Forensics and Security,E007,2(4):683 -696.
  • 5Kirbiz S, Celik M, Lemma A, et al. Forensic watermarking during AAC playback[C]//IEEE International Conference on Mul timedia and Expo. Beijing, China:IEEE Computer Society Press, 2007:1111 -1114.
  • 6Singh l.,Sridharan S. Speech enhancement for forensic applications using dynamic time warping and wavelel packet analysis [C]//TENON'97, IEEE Region 10 Annual Conference. Brisbane, Australia : 1EEE Computer Society Press ,1997(2): 475 -478.
  • 7Ortega Garcia J, Cruz-Lianas S, (;onzalez-Rodrigucz J. Speech variability in automatic speaker recugnitinn systems fur forensic purposes[C]//IEEE 33rd Annual 1999 International Carnahan Conference on Security Technology. Madrid, St}ain : IEEF Computer Society Press , 1999:327-331.
  • 8Grigoras {2. Digital audio recording analysis: The electric nelwork frequency(ENF) criterion[J]. Int J Speech Language Law. 2005,12(1):68 -76.
  • 9Rodriguez l) P N, Apolinario J A, Biscainho L W P. Audio authenticity: Detecting ENF discontinuity wid high precision phase analysis[J]. IEEE Transactions on Information Forensics and Security, 2015 (3) = 534 543.
  • 10Gulbis M, Muller E,Steinebach M. Audio integrity protection and falsification estimation by embedding muhiple watermarks [C]//International Conference on Intelligent Information Hiding and Multimedia Signal Processing,IIH MSP 06. Pasadena, CA, United States : IEEECircuits and Systems SocielyPress,2006:469- 472.

引证文献2

二级引证文献8

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部