Open AccessLocating secret messages based on quantitative steganalysis
Author(s) -
Ching-Nung Yang,
Fenlin Liu,
Shuangkui Ge,
Jicang Lu,
Jie Huang
Publication year - 2019
Publication title -
mathematical biosciences and engineering
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 0.451
H-Index - 45
eISSN - 1551-0018
pISSN - 1547-1063
DOI - 10.3934/mbe.2019247
Subject(s) - steganalysis , steganography , computer science , embedding , artificial intelligence , data mining , computer security , pattern recognition (psychology)
Steganography poses a serious challenge to forensics because investigators cannot identify even traces of secret messages embedded using a steganographer. Contrarily, the objective of locating steganalysis is to locate the embedded message, which should help extract the secret message. In this paper, a methodology of locating steganalysis using quantitative steganalysis is presented for multiple stego images with embedded messages along the same embedding path. Three typical quantitative steganalysis methods are applied to the methodology to locate the messages embedded using LSB re-placement. Experimental results show that the presented methods can reliably estimate the embedding positions, which verifies the validity of the presented methodology. The presented methodology points out a new use of quantitative steganalysis, and further demonstrates that it is necessary to design more precise quantitative steganalysis methods.