STABYLO: steganography with adaptive, Bbs, and binary embedding at low cost

A new steganographic method called STABYLO is introduced in this research work. Its main advantage is to be much lighter than the so-called HUGO, WOW, and UNIWARD schemes, the state of the art steganographic processes. To achieve the proposed goal, famous experimented components of signal processing, coding theory, and cryptography are combined together, leading to a scheme that can reasonably face up-to-date steganalysers.

[1]  Sorina Dumitrescu,et al.  Detection of LSB Steganography via Sample Pair Analysis , 2002, Information Hiding.

[2]  Ching-Yu Tyan,et al.  Image processing-enhancement, filtering and edge detection using the fuzzy logic approach , 1993, [Proceedings 1993] Second IEEE International Conference on Fuzzy Systems.

[3]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[4]  Jessica J. Fridrich,et al.  Universal distortion function for steganography in an arbitrary domain , 2014, EURASIP Journal on Information Security.

[5]  Manuel Blum,et al.  An Efficient Probabilistic Public-Key Encryption Scheme Which Hides All Partial Information , 1985, CRYPTO.

[6]  Dana S. Richards,et al.  Modified Matrix Encoding Technique for Minimal Distortion Steganography , 2006, Information Hiding.

[7]  Jessica J. Fridrich,et al.  Ensemble Classifiers for Steganalysis of Digital Media , 2012, IEEE Transactions on Information Forensics and Security.

[8]  Andrew D. Ker.  A General Framework for Structural Steganalysis of LSB Replacement , 2005, Information Hiding.

[9]  Weiwei Liu,et al.  Syndrome trellis codes based on minimal span generator matrix , 2014, Ann. des Télécommunications.

[10]  Xinpeng Zhang,et al.  Adaptive JPEG steganography with new distortion function , 2014, Ann. des Télécommunications.

[11]  Jiwu Huang,et al.  Edge Adaptive Image Steganography Based on LSB Matching Revisited , 2010, IEEE Transactions on Information Forensics and Security.

[12]  Jessica J. Fridrich,et al.  Steganalysis of LSB Replacement Using Parity-Aware Features , 2012, Information Hiding.

[13]  Tomás Pevný,et al.  Modern steganalysis can detect YASS , 2010, Electronic Imaging.

[14]  Tomás Pevný,et al.  Using High-Dimensional Image Models to Perform Highly Undetectable Steganography , 2010, Information Hiding.

[15]  Jessica J. Fridrich,et al.  Designing steganographic distortion using directional filters , 2012, 2012 IEEE International Workshop on Information Forensics and Security (WIFS).

[16]  Jessica J. Fridrich,et al.  Minimizing Additive Distortion in Steganography Using Syndrome-Trellis Codes , 2011, IEEE Transactions on Information Forensics and Security.

[17]  Tomás Pevný,et al.  Statistically undetectable jpeg steganography: dead ends challenges, and opportunities , 2007, MM&Sec.

[18]  Jessica J. Fridrich,et al.  Steganalysis in high dimensions: fusing classifiers built on random subspaces , 2011, Electronic Imaging.

[19]  J. Mielikainen.  LSB matching revisited , 2006, IEEE Signal Processing Letters.

[20]  Caroline Fontaine,et al.  A Survey of Homomorphic Encryption for Nonspecialists , 2007, EURASIP J. Inf. Secur..

[21]  Manuel Blum,et al.  Comparison of Two Pseudo-Random Number Generators , 1982, CRYPTO.

[22]  Bin Li,et al.  Textural features based universal steganalysis , 2008, Electronic Imaging.

[23]  Chin-Chen Chang,et al.  High payload steganography mechanism using hybrid edge detector , 2010, Expert Syst. Appl..

[24]  Jessica J. Fridrich,et al.  Reliable detection of LSB steganography in color and grayscale images , 2001, MM&Sec '01.

[25]  Andreas Westfeld,et al.  F5-A Steganographic Algorithm , 2001, Information Hiding.

[26]  Sorina Dumitrescu,et al.  LSB steganalysis based on high-order statistics , 2005, MM&Sec '05.