Secure data hiding by fruit fly optimization improved hybridized seeker algorithm

The recent growth of World Wide Web (WWW) and development of the next-generation internet facilitates a huge amount of data being conveniently transmitted via wireless networks. The sensitive information transmitted is potentially vulnerable in the communication channel like wireless networks. Unauthorized users could potentially intercept and negatively exploit the true intent of the information being exchanged between legitimate users. The efficient steganography techniques are very useful to prevent such undesirable interception of information. In this work, we propose and evaluate an efficient image steganography using Fruit Fly Optimization hybridized Improved Seeker (FOIS) algorithm. The FOIS provides information security and safeguards the medical data to avoid medical related cybercrimes. FOIS efficiently determines the optimal locations of pixels adaptively in the spatial domain of the cover image. Initially, the cover image is divided into n blocks of 8 x 8, on which a permutation combination is applied to find the number of blocks for further processing. This method improves the image quality and secures data. The secret messages are embedded in each block using optimal pixels selection and Least Significant Bit (LSB) of Discrete Cosine Transform coefficients. Moreover, in order to ensure seamless communication over an insecure communication channel, a dual cryptosystem model is developed which consist of the proposed steganography scheme and Rivest Cipher (RC4) cryptosystem. This work validates the security level of the stego image, and finally the performance is compared with state-of-the-art methods such as LSB, Particle Swarm Optimization and Genetic Algorithm. The performance assessment reveals that the proposed steganography model outperforms other optimization based approaches in terms of Peak Signal-to-Noise Ratio, embedding capacity and imperceptibility.