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Article type: Research Article
Authors: K, Vijaya; * | Jayashree, K.b
Affiliations: [a] Department of Computer Science and Engineering, Rajalakshmi Engineering College, Chennai, India | [b] Department of Artificial Intelligence and Data Science, Panimalar Engineering College, Chennai, India
Correspondence: [*] Corresponding author: Vijay K, Department of Computer Science and Engineering, Rajalakshmi Engineering College, Chennai, India. E-mail: [email protected]
Abstract: Content-Based Image Retrieval (CBIR) uses complicated algorithms to analyze visual attributes and retrieve relevant photos from large databases. CBIR is essential to a privacy-preserving feature extraction and protection method for outsourced picture representation. SecureImageSec combines essential methods with the system’s key entities to ensure secure, private and protected image feature processing during outsourcing. For a system to be implemented effectively, these techniques must be seamlessly integrated across critical entities, such as the client, the cloud server that is being outsourced, the component that protects secure features, the component that maintains privacy in communication, access control, and authorization, and the integration and system evaluation. The client entity initiates outsourcing using advanced encryption techniques to protect privacy. SecureImageSec protects outsourced data by using cutting-edge technologies like Fully Homomorphic Encryption (FHE) and Secure Multi-Party Computation (SMPC). Cloud servers hold secure feature protection entities and protect outsourced features’ privacy and security. SecureImageSec uses AES and FPE to protect data format. SecureImageSec’s cloud-outsourced privacy-preserving communication uses SSL/TLS and QKD to protect data transmission. Attribute-Based Encryption (ABE) and Functional Encryption (FE) in SecureImageSec limit access to outsourced features based on user attributes and allow fine-grained access control over decrypted data. SecureImageSec’s Information Leakage Rate (ILR) of 0.02 for a 1000-feature dataset shows its efficacy. SecureImageSec also achieves 4.5 bits of entropy, ensuring the encrypted feature set’s muscular cryptographic strength and randomness. Finally, SecureImageSec provides secure and private feature extraction and protection, including CBIR capabilities, for picture representation outsourcing.
Keywords: Content-based image retrieval, Homomorphic Encryption, SecureImageSec, Quantum Key Distribution, Cloud computing
DOI: 10.3233/IDA-240265
Journal: Intelligent Data Analysis, vol. Pre-press, no. Pre-press, pp. 1-22, 2024
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