Blockchain Data Privacy Protection Method Based on Intelligent Collaborative Computing
Yiping Chen, Fengshan Yuan · 2022
With the increasing maturity of blockchain technology, more and more systems use blockchain as the underlying architecture. And the ever-increasing number of loT devices also generate massive amounts of data. There is no doubt that these data will generate greater data value when they are collaboratively processed and shared. Considering that these data belong to different entities or individuals, using secure multi-party computing to design a data processing and sharing scheme can well take into account the two requirements of data security and privacy protection. The main purpose of this paper is to conduct research on blockchain data privacy protection methods based on intelligent collaborative computing. Based on Paillier algorithm, this paper optimizes its decryption process and reduces the decryption time of the homomorphic encryption process. In the experiment of testing the algorithm scheme, the experimental results show that the key generation time of various key lengths is tested for the proposed scheme, and the results show that the key generation time increases almost linearly with the increase of the key length.