A Unified Attribute-Based Encryption Data Sharing Scheme Matching Industrial Internet Framework

The Industrial Internet is the combination of traditional industry and Internet technology to achieve intelligent, automated, information-based, and networked production modes. From the closed industrial environment to the open Internet network environment, data sharing in the industrial scenario is facing various risks brought by an open network. Ciphertext policy attribute-based encryption (CP-ABE) can guarantee industrial data confidentiality while achieving precise and flexible access control. However, the current CP-ABE schemes cannot fully meet the requirements of the Industrial Internet, due to inefficient algorithms, incomplete functionality, poor dynamic monitoring capability, and separation from the Industrial Internet framework. Therefore, this article proposes a unified CP-ABE data security sharing scheme matching the Industrial Internet framework. To decrease the local calculation cost of the industrial device, outsourced encryption is implemented by using multiple computing nodes to encrypt the subkeys, respectively. Online/offline encryption can be outsourced to computing nodes. Attribute revocation can efficiently update the revoked user's private key. Search-related costs are all constant. To enhance the dynamic monitoring, trust is set as an attribute and is updated adaptively in time through the attribute revocation algorithm. To further improve the security of data sharing, encapsulation is combined with on-chain ciphertext storage, which not only prevents symmetric ciphertext from being stolen and tampered with but also modifies the ciphertext component of the key ciphertext as needed. The scheme also realizes functions, including outsourced decryption and policy hiding. The scheme can resist the chosen plaintext and keyword attack, and ensure the forward and backward security of attribute revocation. By analysis and experiment, although our scheme achieves massive functions, it also has excellent algorithm efficiency.