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Steganography Image Security Using Enhanced Hyperactive Cryptography Model

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Artificial Intelligence Based Smart and Secured Applications (ASCIS 2025)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 2822))

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Abstract

Steganographic image security technology can be used to conceal sensitive data within digital images without any visible alteration, thereby ensuring the confidentiality of sensitive data. In the proposed work process, encryption encrypts the message, converts it to ciphertext, and decryption recovers the original message through insecure key verification. Traditional encryption and decryption methods suffer from poor key management, susceptibility to brute-force attacks, or vulnerability to steganalysis. To address these threats, the system employs an enhanced key verification algorithm, the Enhanced Hyperactive Encryption Method (EHACM), which dynamically generates encryption keys and improves their resistance to attacks. The message payload is encrypted and embedded in the least significant bits of the ciphertext image, called Secret Message Least Significant Bits (SM-LSBs). This payload capacity is powerful in terms of invisibility. Keyed Elliptic Curve Cryptography (K-ECC) is used to provide secure key exchange, while Elliptic Curve Diffie-Hellman (ECDH) is used to give a strong shared secret. This model integrates EHACM, SM-LSB, K-ECC and ECDH to achieve improved confidentiality, resilience, secure recovery and overall image security in steganography.

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Correspondence to Sreena G. Nair .

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Nair, S.G., Rohini, K. (2026). Steganography Image Security Using Enhanced Hyperactive Cryptography Model. In: Rajagopal, S., Sajja, P., Thanki, R., Kumar, A. (eds) Artificial Intelligence Based Smart and Secured Applications. ASCIS 2025. Communications in Computer and Information Science, vol 2822. Springer, Cham. https://doi.org/10.1007/978-3-032-17843-5_12

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  • DOI: https://doi.org/10.1007/978-3-032-17843-5_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-032-17842-8

  • Online ISBN: 978-3-032-17843-5

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