###### Abstract  
The cloud provides on-demand, high-quality services to its users without the burden of managing hardware and software. Though the users benefit from the remote services provided by the cloud, they do not have their personal data in their physical possession. This certainly poses new security threats for personal and confidential data, bringing the focus back on trusting the use of the cloud for sensitive data. The benefits of the cloud outweigh the concerns raised earlier, and with an increase in cloud usage, it becomes more important for security services to evolve in order to address the ever-changing threat landscape. Advanced encryption standard (AES), being one of the most widely used encryption techniques, has inherent disadvantages related to the secret key that is shared, and predictable patterns in subkey generation. In addition, since cloud storage involves data transfer over a wireless channel, it is important to address the effect of noise and multipath propagation on the transmitted data. Catering to this problem, we propose a new approach--the secure and reliable neural cryptcoding (SARNC) technique--which provides a superior algorithm, dealing with better encryption techniques combined with channel coding. A chain is as strong as the weakest link and, in the case of symmetric key encryption, the weakest link is the shared key. In order to overcome this limitation, we propose an approach wherein the key used for cryptographic purposes is different from the key shared between the sender and the receiver. The shared key is used to derive the secret private key, which is generated by the neural key exchange protocol. In addition, the proposed approach emphasizes strengthening the sub-key generation process and integrating advanced encryption standard (AES) with low-density parity check (LDPC) codes to provide end-to-end security and reliability over wireless channels. The proposed technique was tested against research done in related areas. A comparative study shows a significant improvement in PSNR, MSE, and the structural similarity index (SSIM). The key strength analysis was carried out to understand the strength and weaknesses of the keys generated. cloud computing; image; neural key exchange protocol; LDPC coding; cryptcoding; subkey; Khazad function; security; reliability +
Footnote †: journal: Accepted: 20 April 2023  
the military, and medicine. Around 70% of internet traffic is dominated by images. As per the IBM Cost of Data Breach Report 2022, 45% of data breaches are cloud-based. The average time taken to find and prevent a data breach is 277 days. This reinforces the need to take a fresh look at security, especially involving sensitive information, since the security provided by cloud service providers (CSP) [1] has not stopped frequent security breaches adversely impacting organizations and users. Numerous theories and techniques have been proposed to tackle the problem of data security. Encryption, steganography, and watermarking techniques [2] are widely used to secure the images. Among these, encryption is the most efficient and commonly used method. One of the approaches to protect the privacy and integrity of outsourced data is to encrypt it before storing it in the cloud [3,4]. Users can upload an encrypted file that is foolproof from any tampering. Security is always considered a shared responsibility between two parties. The focus is shifting towards users taking control of certain aspects of security, thus protecting sensitive personal identifiable information (PII), while CSP enables the platform to store and share the data. In line with that principle, we propose an approach that empowers users to take control of securing the images involving sensitive information. The approach extends the concepts of bring your own key (BYOK), in conjunction with bring your own algorithm (BYOA). It further adds additional controls, which ensure that the key provided by the users is different from the key used for encrypting the images.