Biblio

Chinese Remainder Theorem (CRT) is one of the spatial domain methods that is more implemented in the data hiding method watermarking. CRT is used to improve security and imperceptibility in the watermarking method. CRT is rarely studied in studies that discuss steganographic images. Steganography research focuses more on increasing imperceptibility, embedded payload, and message security, so methods like LSB are still popular to be developed to date. CRT and LSB have some similarities such as default payload capacity and both are methods in the spatial domain which can produce good imperceptibility quality of stego image. But CRT is very superior in terms of security, so CRT is also widely used in cryptographic algorithms. Some ways to increase imperceptibility in image steganography are edge detection and spread spectrum embedding. This research proposes a combination of edge detection techniques and spread-spectrum embedding based on the CRT method to produce imperceptibility and safe image steganography method. Based on the test results it is proven that the combination of the proposed methods can increase imperceptibility of CRT-based steganography based on SSIM metric.

Detection and prevention of data breaches in corporate networks is one of the most important security problems of today's world. The techniques and applications proposed for solution are not successful when attackers attempt to steal data using steganography. Steganography is the art of storing data in a file called cover, such as picture, sound and video. The concealed data cannot be directly recognized in the cover. Steganalysis is the process of revealing the presence of embedded messages in these files. There are many statistical and signature based steganalysis algorithms. In this work, the detection of steganographic images with steganalysis techniques is reviewed and a system has been developed which automatically detects steganographic images in network traffic by using open source tools.