Volume 19 • Issue 1 • PP: 108-116 • 2025
AI-Driven Cryptographic and Steganographic Integration for Enhanced Text Security Using OpenAI API
Open Access & Copyright
© 2025 The Author(s). Published by ASPG. This article is licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0).
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Artificial Intelligence (AI) can become a great asset to produce cryptographic keys in order to improve the security of the encryption methods. While using machine learning algorithms AI can generate most complex and unpredictable keys to prevent brute-force and cryptanalyst attacks. Key generation using AI also allows the design of cryptographic solutions that adapt to the context in which the key is used. It also enhances the conventional security measures while simultaneously providing great opportunities for creating flexible security solutions. This paper proposed a new text security method based on the integration of the cryptography and steganography, where the suggested method is done based on OpenAI API. The proposed method is consisted of three steps, and these steps are key generation, text encryption, and data embedding. The first step, is utilized by using GPT-2 model to generate set of keys for both cryptography and steganography steps. The second step, is starting by converting the plaintext to ASCII format, then performed modulo arithmetic operation between ASCII values and the keys that generated from the previous step, then convert the achieved equation results to Hexadecimal format, and finally convert these values to binary and these values represent the final ciphertext. The last step of the proposed method is done by hiding the binary values within image, this done by select positions randomly, then used GPT-2 model to generate another set of keys to shift the values of random positions, then applied least significant bit (LSB) algorithm to hide the bits within the final position with different color channels. The proposed approach provides a basis for the development of new-generation secure communication systems in the context of AI.
Keywords
References
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