A Robust Steganographic Algorithm based on Linear Fractional Transformation and Chaotic Maps

• Published in: International journal of advanced computer science & applications 2023, Vol.14 (3)
• Main Authors: Ramzan, Muhammad, Khan, Muhammad Fahad
• Format: Article
• Language: English
• Subjects: Algorithms; Chaos theory; Cryptography; Embedding; Encryption; Entropy (Information theory); Homogeneity; Image compression; Image degradation; Robustness; Signal to noise ratio; Steganography; Substitutes
• ISSN: 2158-107X; 2156-5570
• DOI: 10.14569/IJACSA.2023.0140351

The fundamental objectives of a steganographic technique are to achieve both robustness and high-capacity for the hidden information. This paper proposes a steganographic algorithm that satisfies both of these objectives, based on enhanced chaotic maps. The algorithm consists of two phases. In the first phase, a cryptographic substitution box is constructed using a novel fusion technique based on logistic and sine maps. This technique overcomes existing vulnerabilities of chaotic maps, such as frail chaos, finite precision effects, dynamical degradation, and limited control parameters. In the second phase, a frequency-domain-based embedding scheme is used to transform the secret information into ciphertext by employing the substitution boxes. The statistical strength of the algorithm is assessed through several tests, including measures of homogeneity, correlation, mean squared error, information entropy, contrast, peak signal-to-noise ratio, energy, as well as evaluations of the algorithm's performance under JPEG compression and image degradation. The results of these tests demonstrate the algorithm's robustness against various attacks and provide evidence of its high-capacity for securely embedding secret information with good visual quality.