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  • This paper presents a method for detection of steganographic methods that embed in the spatial domain by adding a low-amplitude independent stego signal, an example of which is least significant bit (LSB) matching. First, arguments are provided for modeling the differences between adjacent pixels using first-order and second-order Markov chains. Subsets of sample transition probability matrices are then used as features for a steganalyzer implemented by support vector machines. The major part of experiments, performed on four diverse image databases, focuses on evaluation of detection of LSB matching. The comparison to prior art reveals that the presented feature set offers superior accuracy in detecting LSB matching. Even though the feature set was developed specifically for spatial domain steganalysis, by constructing steganalyzers for ten algorithms for JPEG images, it is demonstrated that the features detect steganography in the transform domain as well.
  • This paper presents a method for detection of steganographic methods that embed in the spatial domain by adding a low-amplitude independent stego signal, an example of which is least significant bit (LSB) matching. First, arguments are provided for modeling the differences between adjacent pixels using first-order and second-order Markov chains. Subsets of sample transition probability matrices are then used as features for a steganalyzer implemented by support vector machines. The major part of experiments, performed on four diverse image databases, focuses on evaluation of detection of LSB matching. The comparison to prior art reveals that the presented feature set offers superior accuracy in detecting LSB matching. Even though the feature set was developed specifically for spatial domain steganalysis, by constructing steganalyzers for ten algorithms for JPEG images, it is demonstrated that the features detect steganography in the transform domain as well. (en)
Title
  • Steganalysis by Subtractive Pixel Adjacency Matrix
  • Steganalysis by Subtractive Pixel Adjacency Matrix (en)
skos:prefLabel
  • Steganalysis by Subtractive Pixel Adjacency Matrix
  • Steganalysis by Subtractive Pixel Adjacency Matrix (en)
skos:notation
  • RIV/68407700:21230/10:00173901!RIV11-MSM-21230___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(ME10051), V, Z(MSM6840770038)
http://linked.open...iv/cisloPeriodika
  • 0
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 290055
http://linked.open...ai/riv/idVysledku
  • RIV/68407700:21230/10:00173901
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • steganographic methods; LSB matching (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...odStatuVydavatele
  • US - Spojené státy americké
http://linked.open...ontrolniKodProRIV
  • [5261110E81B0]
http://linked.open...i/riv/nazevZdroje
  • IEEE Transactions on Information Forensics and Security
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...v/svazekPeriodika
  • 2
http://linked.open...iv/tvurceVysledku
  • Pevný, Tomáš
  • Fridrich, J.
  • Bas, T.
http://linked.open...ain/vavai/riv/wos
  • 000277777200002
http://linked.open...n/vavai/riv/zamer
issn
  • 1556-6013
number of pages
http://localhost/t...ganizacniJednotka
  • 21230
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