Imperceptible Steganography Scheme with High Payload Capacity using Genetic Algorithm and Particle Swarm Optimization
Pratik D. Shah1, Rajankumar S. Bichkar2

1Pratik D. Shah*, Research Scholor Dept. of E&TC, G. H. Raisoni College of Engineering and Management, Assistant Professor Dr. D. Y. Patil School of Engineering, Savitribai Phule Pune University, Pune, India.
2Rajankumar S. Bichkar, Principal, Vidya Pratishthan’s Kamalnayan Bajaj Institute of Engineering and Technology, Baramati, Savitribai Phule Pune University, Pune, India.
Manuscript received on September 27, 2019. | Revised Manuscript received on October 15, 2019. | Manuscript published on October 30, 2019. | PP: 917-923 | Volume-9 Issue-1, October 2019 | Retrieval Number: A9423109119/2019©BEIESP | DOI: 10.35940/ijeat.A9423.109119
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Abstract: Security is the most significant parameter in all type of confidential data transfers. Steganography is used to enhance the security of such confidential communications. Steganography is a method of covert communication in which the existence of secrecy is concealed. In image steganography, achieving high data embedding capacity and simultaneously retaining good visual quality is a very tricky and difficult objective. In this paper, a reversible, secure, extremely imperceptible and high payload capacity steganography technique in the spatial domain is proposed. The proposed method employs evolutionary computation techniques to identify the most optimum locations and arrangements for secret data embedding. The proposed technique uses Particle Swarm Optimization to find the best possible order of data hiding whereas Genetic algorithm is used to identify the best possible arrangements to modify secret data to produce least amount of change in cover-image. The result of the proposed scheme is compared with many steganography techniques and the proposed scheme outperforms the existing schemes in terms of imperceptibility. The proposed technique produces an average PSNR value of 46.40 dB at 2 bit per pixel data embedding rate.
Keywords: Data Hiding, Genetic Algorithm (GA), Image Steganography, Particle Swarm Optimization (PSO).