Open AccessSteganalysis of Low Embedding Rates LSB Speech Based on Histogram Moments in Frequency Domain
Author(s) -
Yang Wanxia,
Tang Shanyu,
Li Miaoqi,
Cheng Yongfeng,
Zhou Zhili
Publication year - 2017
Publication title -
chinese journal of electronics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.267
H-Index - 25
eISSN - 2075-5597
pISSN - 1022-4653
DOI - 10.1049/cje.2017.09.026
Subject(s) - steganalysis , histogram , embedding , frequency domain , least significant bit , mathematics , domain (mathematical analysis) , speech recognition , computer science , pattern recognition (psychology) , artificial intelligence , statistics , steganography , image (mathematics) , mathematical analysis
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%.