Enhanced IoT Security for Healthcare: A Lionized Remora Optimization-Based Image Encryption Algorithm with Chaotic Maps

Storing and safely transmitting data, however, is a basic obstacle that contemporary healthcare management systems encounter. Consequently, in order to encrypt sensitive data and decrease privacy breaches and cyber-attacks caused by unautho-rised users and hackers, this research suggests a new bit-level image encryption technique based on chaotic maps (BCIEA). Our new Internet of Things (IoT) layered approach incorporates generic and extended components for privacy and security, as well as the ability to identify layer. Furthermore, it was discovered that the BCIEA description lacks rigour, leading to undecipherable algorithm specifics. To bypass the confusion module's dynamic mechanism, the technique first converts the all-zero ciphertext into a diffusion-only procedure, and then selects a cypher image whose sum value is equal to the target cypher image. The results of the experiment indicate that the produced secret keys are adequately unique and random to adequately secure the data kept in contemporary healthcare management systems. Time spent encrypting and decrypting data is reduced, and privacy is enhanced, using the suggested method. The proposed method is more efficient and cheaper than its predecessors, according to this study. It also reduces execution time