Digital watermarking based on chaotic map and reference register
Pattern Recognition
Learning classifier system ensemble and compact rule set
Connection Science - Evolutionary Learning and Optimisation
GA-Based Robustness Evaluation Method for Digital Image Watermarking
IWDW '07 Proceedings of the 6th International Workshop on Digital Watermarking
Watermarking robustness evaluation based on perceptual quality via genetic algorithms
IEEE Transactions on Information Forensics and Security
Genetic algorithm based steganography using wavelets
ICISS'07 Proceedings of the 3rd international conference on Information systems security
Improved adaptive LSB steganography based on chaos and genetic algorithm
EURASIP Journal on Advances in Signal Processing - Special issue on advanced image processing for defense and security applications
A high throughput system for intelligent watermarking of bi-tonal images
Applied Soft Computing
Robust copyright marking using Weibull distribution
Computers and Electrical Engineering
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Steganalytic techniques are used to detect whether an image contains a hidden message. By analyzing various image features between stego-images (the images containing hidden messages) and cover-images (the images containing no hidden messages), a steganalytic system is able to detect stego-images. In this paper, we present a new concept of developing a robust steganographic system by artificially counterfeiting statistic features instead of the traditional strategy by avoiding the change of statistic features. We apply genetic algorithm based methodology by adjusting gray values of a cover-image while creating the desired statistic features to generate the stego-images that can break the inspection of steganalytic systems. Experimental results show that our algorithm can not only pass the detection of current steganalytic systems, but also increase the capacity of the embedded message and enhance the peak signal-to-noise ratio of stego-images.