According　to　Cachin＇s　steganography　security　criterion,　if　the　statistical　distributions　of　cover　and　stego　images　are　identical,　the　hidden　message　is　assumed　undetectable.　However,　any　steganographic　method　will　surely　cause　some　statistical　distortions,　which　gives　steganalyst　a　hint.　This　paper　presents　a　steganalysis　method　for　JPEG　images　based　on　Cachin　criterion.　It　estimates　the　cover　image　from　the　stego　one　by　using　a　small-scale　geometrical　transform,　and　then　detects　the　statistical　distortions　between　the　cover　and　stego　images　based　on　some　features,　which　are　sensitive　to　the　steganographic　modifications.　Then　a　classifier　is　trained　on　these　features.　Three　different　modern　steganographic　schemes　are　tested.　Experimental　results　show　that　the　proposed　steganalysis　scheme　has　better　performance　compared　to　the　current　steganalysis　methods.　©　Springer-Verlag　Berlin　Heidelberg　2007.