In blockchain data validation and query scenarios constructed with Merkle tree data structures, the uneven frequency of data block queries may lead to high communication complexity. This paper introduces the commonly utilized Huffman tree structure from the fields of encoding and compression into the blockchain context and innovatively proposes a blockchain data verification and query scheme based on the construction of binary Huffman trees. The scheme leverages a weight allocation mechanism during the Huffman tree construction process, positioning frequently validated and queried data blocks closer to the root level. This approach shortens their validation paths and reduces the overall communication complexity. Compared with query validation methods that are based on Merkle tree data structures, the Huffman tree-based scheme has higher efficiency and lower resource consumption in scenarios with significant probability disparities. Taking the selective disclosure verification of distributed identity credentials in blockchain as an example, this paper provides a concrete scheme demonstration. Additionally, this scheme can be applied to various blockchain application scenarios, such as leader node selection under weighted voting consensus nodes, smart contract user permission management, and nonsensitive data queries in notarization, thereby enhancing blockchain system performance. This research offers new perspectives and methodologies for improving the efficiency of data validation in blockchain environments.