Detecting LSB Steganography in Color and Gray-Scale Images
IEEE MultiMedia
A new approach to reliable detection of LSB steganography in natural images
Signal Processing - Special section: Security of data hiding technologies
Effective Steganalysis Based on Statistical Moments of Wavelet Characteristic Function
ITCC '05 Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC'05) - Volume I - Volume 01
United-Judgment Methods Based on Parameter-Estimation for Image Steganalysis
MINES '09 Proceedings of the 2009 International Conference on Multimedia Information Networking and Security - Volume 01
Steganalysis Based on Regression Model and Bayesion Network
MINES '09 Proceedings of the 2009 International Conference on Multimedia Information Networking and Security - Volume 01
IH'04 Proceedings of the 6th international conference on Information Hiding
An improved sample pairs method for detection of LSB embedding
IH'04 Proceedings of the 6th international conference on Information Hiding
Assessment of steganalytic methods using multiple regression models
IH'05 Proceedings of the 7th international conference on Information Hiding
Improving steganalysis by fusion techniques: a case study with image steganography
Transactions on Data Hiding and Multimedia Security I
IWDW'06 Proceedings of the 5th international conference on Digital Watermarking
Detection of LSB steganography via sample pair analysis
IEEE Transactions on Signal Processing
Steganalysis using higher-order image statistics
IEEE Transactions on Information Forensics and Security
A feature-based classification technique for blind image steganalysis
IEEE Transactions on Multimedia
Hi-index | 0.00 |
In order to synthetically utilize multiple steganalytic algorithms, and further improve the detection accuracy and enhance detection reliability, United-Judgment methods are researched and analyzed in this paper. According to the performance of each algorithm, United-Judgment methods for both blind and specific steganalysis are proposed based on parameter-estimation and algorithm-selection. Experiments are carried out for the former with seven typical blind detections and the latter one with five typical spatial domain steganalytic methods. Experimental results show that the proposed methods can synthetically utilize the existing multiple algorithms effectively, and achieve more reliable detection.