Ensuring Secure Healthcare Data Storage with ANFIS and CP-ABE in Cloud Computing

Cloud-based technologies have brought the healthcare sector to fast adoption for data storage, management, and access. Cloud systems offer one of the best opportunities for scalability, low costs, and interoperability within healthcare networks, while at the same time presenting major security and privacy problems concerning sensitive patient information. Against this backdrop, this paper articulates a secure and intelligent storage framework for healthcare data via the integration of Ciphertext-Policy Attribute-Based Encryption (CP-ABE) with an Adaptive Neuro-Fuzzy Inference System (ANFIS). CP-ABE contributes to data security through very fine-grained access control applied by embedding in the ciphertext an access policy so that only those users who fulfill the attributes defined in the policy can decrypt the ciphertext. Meanwhile, ANFIS tracks access behavior and predicts potentially threatening events through the use of fuzzy and neural network principles, thereby ensuring that resolution against threats is taken early and the policy is adapted accordingly. This system ensures secure healthcare data with files constructed under cloud storage in the aspects of confidentiality, integrity, and availability, thus granting regulatory adherence to such standards as HIPAA. Taken together, experimental results demonstrate superior precision of threat detection and higher security performances compared to standard models. Hence, this solution offers a secure and scalable intelligent healthcare data management platform in the cloud.