Blockchain-Assisted Verifiable and Secure Remote Sensing Image Retrieval in Cloud Environment

Abstract

Secure retrieval of remote sensing images in an outsourced cloud environment garners considerable attention. Since the cloud service provider (CSP) is considered as a semitrusted third party that may return incorrect retrieval results to save computational resources or defraud retrieval fees for profit, it becomes a critical challenge to achieve secure and verifiable remote sensing image retrieval. This article presents a secure retrieval and blockchain-assisted verifiable scheme for encrypted remote sensing images in the cloud environment. In response to the characteristic that geographical objects in remote sensing images with clear category attributes, we design a remote sensing image retrieval method to facilitate secure and efficient retrieval. In addition, we propose a verifiable method combined with blockchain and Merkle trees for checking the integrity and correctness of the storage and retrieval services provided by CSP, which can replace the traditional third-party auditor. The security analysis and experimental evaluation demonstrate the security, verifiability, and feasibility of the proposed scheme, achieving secure remote sensing image retrieval while preventing malicious behavior of CSP.

Blockchain-Based Method for Spatial Retrieval and Verification of Remote Sensing Images

“…The values for execution time, latency, and throughput in the experiments represent the average outcomes from multiple runs. Additionally, the retrieval accuracy of the algorithm was evaluated using precision and recall rates [26,27]. The application's functionalities include the following: batch writing of encoded remote sensing image data, querying a specified number of remote sensing images based on spatial range, and batch querying of remote sensing images by keywords.…”

SDTU-Net: Stepwise-Drop and Transformer-Based U-Net for Subject-Sensitive Hashing of HRRS Images

“…Mainstream data security technologies, such as fragile watermarking [5], cryptographic algorithms [6] and block chain [7], are still insufficient in the integrity authentication of HRRS images. The most prominent performance is that mainstream security technologies implement authentication at binary level.…”

DMCH: A Deep Metric and Category-Level Semantic Hashing Network for Retrieval in Remote Sensing

“…The analysis and utilization of big data play an important role in hazard alerts, emergency response, and so on [2,3]. A notable increase in remote sensing archives has amplified the demand for content-based image retrieval (CBIR) within the field of remote sensing [4][5][6]. A typical CBIR system comprises two key components: visual feature extraction and similarity measurement.…”