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Dmitry S. Zaichenko, Moscow technical University of communications and Informatics, Moscow, Russia, dmitryzaichenko@yandex.ru
Irina S. Sineva, Moscow technical University of communications and Informatics, Moscow, Russia, iss@mtuci.ru

IoT is a new world for connecting object space in the real world with virtual space in a computer environment. To build IoT as an effective service platform, end users need to trust the system. With the growing quantity of information and communication technologies, the need to ensure information security and improve data security is increasing. One of the potential solutions for this are steganographic methods. Steganography based on the least significant bit (LSB) is a popular and widely used method in the spatial domain. The usual methods used in LSB-based steganography are mainly focused on increasing the capacity of embedded information and stealthiness, while the security issue still needs to be addressed, because the LSB attachment is vulnerable to several common data attacks, such as additive attack of white Gaussian noise (AWGN), geometric attacks and others. The proposed work provides an innovative approach to increasing the latent data transfer in the system. Secret information is preliminarily processed using a modified genetic algorithm. This process increases the security of information, because the data cannot be deciphered without knowing the display rule and the private key. Encoded with the help of a genetic algorithm, the bitstream is embedded in the image using the classic LSB algorithm. The proposed method was tested on different images. In addition, the classic LSB methods have also been tested on the same images. It was noted that the proposed method increased the stability of stego-images to attacks due to encryption. In addition, the peak signal-to-noise ratio (PSNR) in stego-images was not increased. Accordingly, the proposed method increased the stability of stego-images.

Keywords: genetic algorithm, anti-jamming coding, steganography, least significant bit method, IoT.


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Information about authors:
Dmitry S. Zaichenko, Master, Moscow technical University of communications and Informatics, Moscow, Russia
Irina S. Sineva, Candidate of physical and mathematical Sciences, associate Professor, Moscow technical University of communications and Informatics, Moscow, Russia