article · Scientific Reports
Cloud networks require robust methods to protect visual data from unauthorised access. A multi-layered image encryption scheme combines neural key exchange, biological computing concepts, and cellular automata to secure multimedia transmission and storage. The process begins with Tree Parity Machines, where communicating users synchronize weight vectors to establish shared encryption keys across the cloud. Image data undergoes an initial layer of protection via DNA coding, with sequences produced by a Mersenne Twister pseudo-random number generator. Next, an SHA-512 cryptographic hash seeds a Rule 30 Cellular Automata to generate a second pseudo-random sequence, which is combined with the image using an XOR operation. This cellular automata system also drives an S-box substitution mechanism for the final encryption stage. Tests indicate high computational efficiency, strong resistance to attacks, and near-ideal statistical randomness.
Visual media sent over cloud services faces continuous interception and tampering risks. Combining machine learning principles with biological and cellular algorithms creates layered, unpredictable defences. This ensures that sensitive photographic records remain private, resilient against cryptanalysis, and structurally altered to deter unauthorised decryption during cloud transit.
The algorithm targets secure, real-time multimedia transmission and storage across cloud platforms. Potential users include cloud storage providers, enterprise communication networks, and digital media platforms seeking enhanced data confidentiality. Because the findings are based on algorithmic design and quantitative performance evaluations, the work represents applied, laboratory-tested research that requires software development and system integration before reaching operational commercial deployment.
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In this article, a novel image encryption algorithm is proposed for the secure transmission and storage of images over the cloud. The robustness of Tree Parity Machines (TPMs) is utilized in conjunction with DNA coding, Mersenne Twister-based DNA sequence generation, SHA-512 seeded Rule 30 Cellular Automata (CA), and S-box construction to achieve comprehensive multi-layered image encryption. The encryption process is initiated through the use of TPMs, which are employed to facilitate secure key exchange among users communicating over the cloud. The weight vectors of the TPMs are utilized as an initial shared symmetric key, and through iterative weight synchronization, the final weights are evolved into the actual encryption keys. DNA coding is then applied as the first layer of encryption. The corresponding DNA sequences are generated using the Mersenne Twister, which is employed as a Pseudo-Random Number Generator (PRNG). Subsequently, the SHA-512 hashing function is used to generate a seed for Rule 30 Cellular Automata, which is further utilized to construct another PRNG. This newly generated PRNG is applied as an additional key in an XOR operation with the image data, thereby providing an extra layer of security. The same CA-based PRNG is also used to construct an S-box, which is applied in the final encryption stage. Excellent results in terms of security, resistance to attacks, and computational efficiency are demonstrated through performance evaluation. The algorithm is shown to possess strong potential for secure and efficient real-time multimedia transmission and storage over the cloud. A significant advancement in secure cloud-based image communication is offered through the integration of TPMs, DNA coding, and CA in this unique encryption scheme. Moreover, quantitative evaluation further confirms the robustness of the proposed scheme, achieving encrypted image entropy of 7.99904, a high NPCR of [Formula: see text] and a UACI of [Formula: see text], reflecting strong sensitivity to plain text variations, while maintaining an MSE of 10141.88 and PSNR of 8.11 dB.
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DOI: 10.1038/s41598-026-66952-w
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