Steganalysis of Low Embedding Rates LSB Speech Based on Histogram Moments in Frequency Domain. Issue 6 (1st November 2017)

• Record Type: Journal Article
• Authors: Yang, Wanxia; Tang, Shanyu; Li, Miaoqi; Cheng, Yongfeng; Zhou, Zhili
• Is Part Of: Chinese journal of electronics. Volume 26:Issue 6(2017)
• Page Start: 1254
• Page End: 1260
• Publication Date: 2017-11-01
• Subjects: Steganalysis -- Statistical moments of histogram -- Wavelet packet decomposition (WPD) -- Voice over IP (VoIP) -- Speech steganography.; feature extraction -- feature selection -- speech processing -- steganography -- wavelet transforms; steganalysis -- wavelet packet transform -- low embedding steganograpy -- histogram moments in frequency domain -- HMFD -- feature selection -- feature extraction -- LSB matching -- embedding rates -- speech signals -- detection performance -- wavelet packet decomposition -- least significant bit -- speech steganography; Electronics -- Periodicals; Electronics -- China -- Periodicals; Electronics; China; Periodicals; 621.38105
• DOI: 10.1049/cje.2017.09.026
• Languages: English
• ISSNs: 1022-4653

Abstract

Abstract : As wavelet packet transform is able to focus on minute change of signals, this study proposes an analytic approach of low embedding steganograpy based on high order Histogram moments in frequency domain (HMFD), which provides a key solution to the feature selection and extraction of HMFD. The detection results are tested with the LSB matching steganograpy of different embedding rates in speech signals, respectively, it is proved that the detection performance with HMFD applied is greater than that of histogram statistical moments. HMFD by Wavelet packet decomposition (WPD) can effectively detect low embedding rates Least significant bit (LSB) speech steganography, its accuracy can be 60.8% while the embedding rate is only 3%.