Secureimagesec: A privacy-preserving framework for outsourced picture representation with content-based image retrieval

Author:

K Vijay1,Jayashree K.2

Affiliation:

1. Department of Computer Science and Engineering, Rajalakshmi Engineering College, Chennai, India

2. Department of Artificial Intelligence and Data Science, Panimalar Engineering College, Chennai, India

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.

Publisher

IOS Press

Reference45 articles.

1. A. Uhl and A. Pommer, Image and video encryption: from digital rights management to secured personal communication, Springer Science & Business Media 15 (2004).

2. Secure image retrieval over untrusted cloud servers;Abdulsada;International Journal of Engineering and Advanced Technology,2013

3. Secure and efficient data retrieval over encrypted data using attribute-based encryption in cloud storage;Koo;Computers & Electrical Engineering,2013

4. A similarity search scheme over encrypted cloud images based on secure transformation;Xia;International Journal of Future Generation Communication and Networking,2013

5. Secure image hiding algorithm using cryptography and steganography;Sharma;IOSR Journal of Computer Engineering (IOSR-JCE) e-ISSN,2013

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