HCSSIR: Hash Code Selection-Based Secure Image Retrieval in a Blockchain Environment

In the context of real-world Internet of Things (IoT) implementations, the delivery of images within blockchain environments is becoming increasingly crucial. However, the multitable hashing technologies currently used for retrieval suffer from considerable redundancy in tables, leading to diminished performance of the distributed system. To address these challenges, we propose a hash code selection-based secure image retrieval (HCSSIR) scheme for data sharing and secure retrieval on the blockchain. First, we introduce a learning-based method to shorten hash codes. Initial long hash codes are generated using locality-sensitive hashing families for high efficiency and accuracy. The most informative hash tables are then selected based on a learning model that has been pretrained on a dataset specifically prepared for this purpose. This approach aims to reduce space and computational requirements, potentially further decreasing time consumption. Next, a cryptographic hierarchical index structure based on the compressed hash codes is designed, along with its construction and searching methods. We also create a secure Hamming distance computation algorithm to preserve the index features and access patterns. Finally, proxy re-encryption is adapted to ensure data availability in multiuser settings. We offer a security analysis to confirm that the HCSSIR scheme effectively protects the privacy of images, indexes, and queries. Furthermore, the proposed selection method achieves an approximate 12.3% enhancement in F1-score for code compression when compared with the cutting-edge method. Additionally, the HCSSIR scheme registers improvements of approximately 27.58% and 56.7% in searching and storage efficiencies, respectively. These results underscore its suitability for real-world IoT applications.