Image security and recognition system
Multimedia files, in the era of today's digital world, have become essential media for data storage, management and transmission. In information security, a breadth of techniques are required for protecting, identifying, extracting and removing secret data. The protection of media has led to research in developing means for data hiding, such as encryption, steganography and watermarking. Among all, steganography, also known as stego, has the advantage of hiding vital information in an imperceptible manner. Contrary to steganography, steganalysis is used to detect, identify, and/or extract hidden information within various media sources. However, when harmful or suspicious data has been identified and cannot be extracted, it is important that the data be altered/destructed from its initial form.
This research focuses on steganography, steganalysis, as well as steganographic content removal on two dimensional signals, i.e., images. In steganography, new image steganography algorithms in collage and fractal image domains which are different from the majority of existing domains are developed. The problem space of image security is extensive, which leads to research in evolving new image features explicit to JPEG image file formats. A pattern recognition system is designed and constructed for the application of steganalysis, which is initially used to properly distinguish clean and stego JPEG images and further identify various embedding methods. This involves the combination of new features and current features, as well as selection of features that results in higher classification accuracy with a properly trained classification model. In order to avoid steganographic content being received, two image denoising algorithms are utilized to remove the hidden content. A front-end graphical user interface is built for the consolidation of image security steganography methods, recognition system and steganographic content removal. This provides an integrated and user-friendly environment for both non-professional users and experienced steganalysts.