The data generated in the Industrial Internet of Things (IIoT) has important research value. In the process of data sharing, data privacy, security, and data availability are important issues that cannot be ignored. This paper proposes a blockchain privacy protection scheme based on zero-knowledge proof to realize the secure sharing of data among data owners, cloud service providers, and semitrusted cloud servers. First, the method of combining zero-knowledge proof and smart contract is used to verify the availability of data between the data owner and the cloud service provider under the premise of protecting data privacy. Second, proxy reencryption technology is used to realize the secure sharing of data among authorized cloud service providers. In addition, data sharing transaction information between multiple parties and data hashes with digital signatures are stored on the blockchain to achieve public and verifiable data sharing information and data validity. Finally, the theoretical analysis of the scheme shows that the scheme meets the confidentiality requirements of security, integrity, and validity.

The emergence of edge computing has improved the real time and efficiency of the Industrial Internet of Things. In order to achieve safe and efficient data collection and application in the Industrial Internet of Things, a lot of computing and bandwidth resources are usually sacrificed. From the perspective of low computing and communication overhead, this paper proposes an efficient privacy protection layered data aggregation scheme for edge computing assisted IIoT by combining the Chinese Remainder Theorem (CRT), improved Paillier homomorphic algorithm, and hash chain technology (edge computing assisted an efficient privacy protection layered data aggregation scheme for IIoT, EE-PPDA). In EE-PPDA, first, a layered aggregation architecture based on edge computing is designed. Edge nodes and cloud are responsible for local aggregation and global aggregation, respectively, which effectively reduces the amount of data transmission. At the same time, EE-PPDA achieves data confidentiality through improved Paillier encryption, ensuring that neither attackers nor semitrusted nodes (e.g., edge nodes and clouds) can know the private data of a single device, and it can resist by simply using hash chains to resist tampering and pollution attacks ensure data integrity. Second, according to the CRT, the cloud can obtain the fine-grained aggregation results of subregions from the global aggregation results, thereby providing fine-grained data services. In addition, the EE-PPDA scheme also supports fault tolerance. Even if some IIoT devices or communication links fail, the cloud can still decrypt incomplete aggregated ciphertexts and obtain the expected aggregation results. Finally, the performance evaluation shows that the proposed EE-PPDA scheme has less calculation and communication costs.

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With the rapid development of information technology, different organizations cooperate with each other to share data information and make full use of data value. Not only should the integrity and privacy of data be guaranteed but also the collaborative computing should be carried out on the basis of data sharing. In this paper, in order to achieve the fairness of data security sharing and collaborative computing, a security data collaborative computing scheme based on blockchain is proposed. A data storage query model based on Bloom filter is designed to improve the efficiency of data query sharing. The MPC contract is designed according to the specific requirements. The participants are rational, and the contract encourages the participants to implement the agreement honestly to achieve fair calculation. A secure multiparty computation based on secret sharing is introduced. The problem of identity and vote privacy in electronic voting is solved. The scheme is analyzed and discussed from storage expansion, anticollusion, verifiability, and privacy.

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