工业区块链中基于CUDA的数据并行处理方法

工业区块链数据交易系统能够使交易双方在没有中间商存在的情况下安全地进行交易，简化了交易流程，降低了交易成本。针对大规模数据上链，现有的一般做法是将源数据的哈希值作为元数据存储到区块链，源数据本身则存储在本地或云端。一方面，传统哈希值的计算方式难以满足工业大规模数据高效上链的需求。另一方面，由于只将元数据存储到了区块链，交易时数据需求者在只收到元数据时无法确认源数据本身是否完整。因此，设计了一种基于CUDA的数据并行处理方法，通过合理的数据分块、线程布局等手段加快大规模工业数据哈希值的计算速度，提高上链效率。并且，基于此方法构建了两方数据完整性验证模型，数据需求者在交易时能够在未得到源数据的情况下，根据证明信息有效地验证源数据的完整性，避免了因传输无用数据而付出的通信代价。对于较大规模工业数据，所提出的计算方法可将哈希值计算效率提升至少22%。同时，由安全性分析可知，在数据拥有者持有签名私钥的特殊情况下，数据需求者在交易时可以对源数据进行完整性验证。

A CUDA-based data-parallel processingmethod in industrial blockchain

The industrial blockchain data transaction system can enable parties to conduct transactions safely without the presence of an intermediary, simplifying the transaction process and reducing transaction costs. For storing industrial large-scale data to blockchain, the current general method is to store the hash value of the source data as metadata to the blockchain, and the source data itself is stored locally or in the cloud. On the one hand, the traditional hash value calculation method is difficult to meet the needs of efficiency for storing industrial large-scale data to blockchain. On the other hand, since only the metadata is stored on the blockchain, the data demander cannot confirm whether the source data itself is complete during the transaction. Therefore, this paper designs a data-parallel processing method based on CUDA, which speeds up the calculation of large-scale industrial data hash value through reasonable data chunking, thread layout and other methods, and improves the efficiency of storing industrial large-scale data to blockchain. Moreover, based on this method, a two-party data integrity verification model is constructed. The data demander can effectively verify the integrity of the source data according to the proof information without obtaining the source data during the transaction, resulting in the reduction of communication cost due to the transmission of useless data. For the large scale industrial data, the proposed calculation method can increase the hash value calculation efficiency by at least 22%. In addition, the security analysis shows that in the special case the data owner holds the signature private key, the data demander can verify the integrity of the source data during the transaction.