ArticleScientific reports2026
A hybrid blowfish-based cryptography and chaotic quantization steganography framework with genetic key generation.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Security is the main attribute when dealing with information exchange. Confidential information theft, data loss, and data manipulation are conceivable results of security events. Different forms of data hiding are Cryptography and Steganography. Cryptography converts information into an unreadable form, and steganography hides the existence of information. The proposed work experiments with Advanced Blowfish Encryption based on an extended round function integrity with Chaotic Image Quantization (ABECIQ) as a security mechanism. ABECIQ aims to introduce a novel security mechanism that combines cryptography and steganography with the key generation scenario using a genetic algorithm. Initially, using a genetic algorithm and real-time clock values, the secret keys are created. The Blowfish algorithm's round function 'F' is modified by adding crossover and mutation functions. The generated ciphertext is embedded in an image using the chaotic-quant technique. The proposed work is analysed using parameters of the Avalanche effect, Entropy values, Execution time, Attack scenario, Correlation coefficient, and Peak Signal-to-Noise Ratio (PSNR) values. The experiments demonstrate that the ABECIQ algorithm achieves PSNR values within the range of 65 to 74 dB while SSIM values are above 0.999, which indicate high imperceptibility. The generated keys also show entropy values which are close to the theoretic maximum of 8 bits per character. In addition, the proposed algorithm shows high throughput thereby indicating improved computational efficiency compared to the existing algorithm. The analysis shows that ABECIQ provides better results than the existing Chaotic, Blowfish Encryption, as well as AES-RDH algorithm. ABECIQ is evaluated with different text files of sizes 4KB and 12KB demonstrating better PSNR, MSE, SSIM, and Correlation Coefficient. In addition, the time complexity for ABECIQ has also been analyzed for embedding process.
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