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Matching a particular image within extensive datasets has become increasingly pressing in many practical fields. Hence, a number of matching methods have been developed when confidential images are used in image matching between a pair of security agencies, but they are limited by either search cost or search precision. In this paper, we propose a privacy-preserving private image matching scheme between two parties where images are confidential, namely secure and efficient private image matching (SEPIM). The descriptor set of the queried party needs to be generated and encrypted properly with the use of a secret key at the queried party side before being transferred to the other party. We present the development and validation of a secure scheme to measure the cosine similarity between two descriptor sets. To hasten the search process, we construct a tree-based index structure by utilizing the k-means clustering algorithm. The method can work without using any image encryption, sharing, and trusted third party. SEPIM is relatively efficient when set against other methods of searching images over plaintexts, and shows a higher search cost of just 14% and reduction in search precision of just 2%. We conducted several empirical analyses on real image collections to demonstrate the performance of our work.

Outsourced data in cloud and computation results are not always trustworthy because data owners lack physical possession and control over the data as a result of virtualization, replication, and migration techniques. Protecting outsourced data from security threats has become a challenging and potentially formidable task in cloud computing; hence, many schemes have focused on ameliorating this problem and on enabling public auditability for cloud data storage security. These schemes drop into two categories: total computation cost and burden on client side. Researchers have used bilinear map technology with public key cryptography. Although this technology is highly efficient, computation time is long and overhead cost is high. The client needs to perform numerous computations to ensure the integrity of data storage. To reduce auditing cost, we propose an efficient and robust scheme to maintain data integrity in cases that involve public auditing. Our scheme adopts modern cipher cryptography with a cryptographic hash function. We consider allowing a third party auditor to preprocess data on behalf of cloud users before uploading them to cloud service providers and then verifying data integrity afterward. Our proposed scheme has important security characteristics, such as privacy, key management, low cost computation, key exchange, low overhead cost, no burden on client side, inability of cloud service providers to create correct verifier respond without data, and one-time key. Finally, efficiency analysis shows that our scheme is faster and more cost-efficient than the bilinear map-based scheme.