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Optimized multimedia data through computationally intelligent algorithms

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Abstract

In the field of data exchange, the security of information is the critical aspect. This void in the security helped the evolution of steganography to address the problem of security, especially when highly critical information exchange is the priority. Better and advanced level of security has been attained using the techniques of steganography with cryptography. However, it has been observed that steganographic techniques principled on computationally intelligent or inspired by nature algorithms are gaining much attention. The paper proposes a method for image steganography in transform domain using hybridization of two computationally intelligent algorithms, i.e., firefly optimization algorithm and ant colony optimization algorithm with Huffman encoding to address the gap of high payload. Comparative analysis of the proposed steganographic tool with other existing methods and analysis of the values obtained against some key performance terms like PSNR (peak signal to noise ratio), MSE (mean square error), BER (bit error rate) and SSI (structural similarity index) determines the proposed algorithm as a powerful method. The proposed tool achieves the PSNR of 68.06 dB and the embedding capacity of 985,682 bits.

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Authors and Affiliations

  1. CSE, Chandigarh University, Mohali, 140413, India

    Neha Sharma & Rajeev Kumar

  2. ECE, Birla Institute of Technology, Jharkhand, India

    Chinmay Chakraborty

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  1. Neha Sharma
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Sharma, N., Chakraborty, C. & Kumar, R. Optimized multimedia data through computationally intelligent algorithms. Multimedia Systems 29, 2961–2977 (2023). https://doi.org/10.1007/s00530-022-00918-6

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