Stretching the Limits of Steganography
Proceedings of the First International Workshop on Information Hiding
A new approach to reliable detection of LSB steganography in natural images
Signal Processing - Special section: Security of data hiding technologies
Edge adaptive image steganography based on LSB matching revisited
IEEE Transactions on Information Forensics and Security
Towards genetic feature selection in image steganalysis
CCNC'10 Proceedings of the 7th IEEE conference on Consumer communications and networking conference
Adaptive image steganography with mod-4 embedding using image contrast
CCNC'10 Proceedings of the 7th IEEE conference on Consumer communications and networking conference
Detection of LSB steganography via sample pair analysis
IEEE Transactions on Signal Processing
Adaptive Data Hiding in Edge Areas of Images With Spatial LSB Domain Systems
IEEE Transactions on Information Forensics and Security
Hidden digital watermarks in images
IEEE Transactions on Image Processing
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Modern information hiding technology plays a vital role in information security. Steganography is the art and science of scripting hidden messages in such a manner that no one, except the sender and directed receiver realise the existence of the message. Image steganography is the most well-liked method for message cover up. In LSBMR, two covert bits is fixed into each embedding unit and the threshold value for region selection is determined. The major disadvantage of this scheme is the total difference is taken as the threshold value. In this paper, LSB matching revisited LSBMR image steganography using genetic algorithm GA is proposed, in which genetic algorithm is used to select the embedding regions according to the size of the secret message and to optimise the threshold value of the selected image regions. Experimental analysis shows that the proposed algorithm outperforms the existing methods in terms of capacity and security.