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All Journal International Journal of Electrical and Computer Engineering
Al-Omari, Hamdi A.
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Computer Science & IT Electrical & Electronics Engineering

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An adaptive audio wave steganography using simulated annealing algorithm Obeidat, Atef Ahmed; Bawaneh, Mohmmed Jazi; Shqair, Sawsan Yousef Abu; Al-Omari, Hamdi A.; Al-shalabi, Emad Fawzi
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 2: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i2.pp2237-2253

Abstract

The science of information security has increased in importance to encounter the espionage and information theft. This research proposes a new steganography framework that utilizes simulated annealing (SA) as an artificial intelligence algorithm to support the process of hiding a binary secret message file within an audio wave file. The best path for embedding the secret data inside the audio file is determined through SA that searches for the preferred path according to the content of the host audio file and secret message to be hidden. The least significant bit (LSB) technique was employed to hide message bytes, in which each audio-chosen byte will hold one bit from a secret message byte. The hiding process constructs the stego audio file and extraction key that will be required in an extraction process. The authorized user requires an extraction key and a decryption key to retrieve the hidden message. On the other hand, the attacker requires knowledge of the aforementioned keys and working algorithms that were employed in the hidden process. Robustness against data extraction, detection, imperceptibility (phonological hearing), security, peak signal to noise ratio (PSNR), mean square error (MSE) and capacity as security performance measures were used to evaluate the system. The maximum size of the data to be hidden may reach 12.5% of the data size of the host audio file, in which the average value of MSE and PSNR are (0.0041, 74.73), respectively.
Co-Authors Al-shalabi, Emad Fawzi Bawaneh, Mohmmed Jazi Obeidat, Atef Ahmed Shqair, Sawsan Yousef Abu