Blockchain stores transaction data in the form of distributed ledger, and its nodes hold copies of current data by storing hash chain. Due to the particularity of the blockchain structure, the number of blocks increases over time and the storage pressure of nodes also increases with the increasing of blocks, so that the storage scalability has become one of the bottlenecks in blockchain development. To address this problem, a blockchain storage expansion model based on Chinese Remainder Theorem (CRT) was proposed. In the model, the blockchain was divided into high-security blocks and low-security blocks, which were stored by different storage strategies. Among them, low-security blocks were stored in the form of network-wide preservation (all nodes need to preserve the data), while the high-security blocks were stored in a distributed form after being sliced by the CRT-based partitioning algorithm. In addition, the error detection and correction of Redundant Residual Number System (RRNS) was used to restore data to prevent malicious node attacking, so as to improve the stability and integrity of data. Experimental results and security analysis show that the proposed model not only has security and fault tolerance ability, but also ensures the integrity of data, as well as effectively reduces the storage consumption of nodes and increases the storage scalability of the blockchain system.

Blockchain technology is widely used in vehicular network, energy internet, smart grid， etc., but attackers can combine social engineering and data mining algorithms to obtain users’ privacy data recorded in the blockchain； especially in microgrid, data generated by games between neighboring energy nodes are more likely to leak user privacy. In order to solve such a problem, based on the alliance blockchain, a secure energy transaction model with a one-to-many energy node account matching mechanism was proposed. The proposed model mainly uses the generation of new accounts to prevent attackers from using data mining algorithms to obtain private data such as energy node accounts, geographical locations, and energy usage from transaction records. The simulation experiment combines the characteristics of the alliance chain, the number of new accounts generated by energy nodes, and the change of transaction verification time to give the analysis results of privacy protection performance, transaction efficiency, and security efficiency. The experimental results show that， the proposed model requires less time during the stage of transaction initiation and verification, has higher security, and the model can hide the transaction trend between adjacent users. The proposed scheme can be well applied to the energy internet transaction scenario.