Achieving lightweight policy-hiding access control and efficient auditing for IoT-based electronic health records in the cloud

The widespread adoption of Internet of Things (IoT) technologies in healthcare has led to the continuous generation of Electronic Health Records (EHRs) that are often outsourced to cloud storage. While cloud platforms offer scalability and availability, they introduce significant challenges in enforcing fine-grained access control, preserving policy privacy, and supporting efficient public auditing over large volumes of IoT-generated data. Existing solutions mainly focus on access authorization and provide limited support for scalable and privacy-preserving auditing. This paper proposes SEC-HIoT , a secure and efficient access control framework for IoT-based EHR systems. Rather than attempting to remove bilinear pairings from ciphertext-policy attribute-based encryption (CP-ABE), which the recent cryptanalysis of pairing-free constructions shows to be unsafe, SEC-HIoT confines them: encryption performs no pairing at all, and the pairings needed for decryption are executed by the fog against a blinded transformation key, so no pairing is ever computed on a resource-constrained device. To protect access policies, the scheme employs a secret-keyed attribute encoding mechanism that achieves attribute-label hiding against dictionary attacks, and the same encoding makes the construction usable over efficient asymmetric pairings. User revocation is handled by a lightweight perturbable mechanism that updates only the ciphertext blinding component and the keys of users who remain authorised, leaving the encrypted payload untouched. For auditing, SEC-HIoT combines Bloom filter–based indexing with Merkle tree verification to enable fast record lookup and lightweight integrity checking, while a blockchain-backed randomized signature mechanism supports both public auditing and owner-resolvable accountability without exposing signer identities. Security analysis establishes confidentiality, unforgeability, attribute-label hiding, and backward secrecy under revocation. A working implementation shows that the device-side decryption cost is independent of policy size at \(\approx \bf 2.3\) ms, a \(\bf 261\times\) reduction over the non-outsourced path at fifty attributes, that the IoT device performs no public-key operation during ingest, and that revoking a user costs a single group exponentiation per record instead of re-encryption.