VPCDIR: Verifiable and Privacy-Preserving Cross-Domain Image Retrieval in Internet of Things

The advancement of cloud computing and Internet of Things (IoT) has driven progress in image-based searchable encryption technology, which meets the escalating security demands of outsourced multimedia data in IoT scenarios. However, existing encrypted image retrieval schemes still face critical challenges, such as lack of cross-domain support, low retrieval efficiency and accuracy, and absence of reliable verifiability. To address these issues, this paper proposes a verifiable and privacy-preserving cross-domain image retrieval scheme (VPCDIR) in IoT. In our scheme, the re-encryption and key transformation technologies are implemented to achieve the availability of cross-domain image retrieval, and the learning with errors (LWE)-based enhanced secure k-nearest neighbor (kNN) algorithm is used to preserve the privacy of image features. Furthermore, the hybrid index mechanism that combines clustering and locality-sensitive hashing (LSH) is designed to enhance retrieval efficiency and accuracy, and the Merkle hash tree (MHT) with the short signature realizes reliable authenticity verification of the retrieval result. Finally, formal security analysis confirms the security of our scheme. Extensive experiments on the real dataset demonstrate the efficiency and practicability of VPCDIR for cross-domain image retrieval in IoT.