ESZF key generation model with novel identity and attribute-based encryption algorithm in secure cloud storage using health care data

Cloud computing and cloud storage have revolutionized data processing and management by improving resource availability and accessibility while reducing operational overhead. In the healthcare sector, electronic health records (EHRs), which contain patients’ medical histories and clinical information, are stored and processed in cloud data centers. Data encryption plays a critical role in healthcare applications by safeguarding sensitive patient information from unauthorized access and ensuring compliance. In the healthcare industry, where confidentiality, integrity, and availability of patient data are paramount, encryption provides a robust layer of protection against data breaches and cyberattacks. Traditional encryption techniques required decryption of the data before computation, potentially exposing sensitive medical information. To address these challenges, this research introduces an Efficient SpinalZFNet (ESZF) Key Generation model with the Identity Attribute Deep Key Honey Encryption (IADKHE) algorithm for secure cloud storage of healthcare data. Initially, identity and attribute information are extracted from EHRs, transformed into an Identity–Attribute Vector through ASCII conversion and secure hashing, and supplied to the ESZF model for cryptographic key generation. The generated key is securely managed and utilized by the IADKHE algorithm to encrypt healthcare records, while a honey message generation mechanism enhances resistance against unauthorized key-guessing attacks. The evaluation outcomes reveal that the developed module achieved encryption time, memory usage, decryption time, key generation time, and throughput values of 8.772ms, 55.253 MB, 12.011ms, 11.642 ms, and 96.938 Mbps, respectively.