Abstract
The increasing production and processing of image data, especially in remote sensing applications, has raised concerns regarding image security, privacy, and efficient retrieval as it is most widely used in sensitive applications. In this article, to address these challenges, a novel privacy-preserving content-based image retrieval (PPCBIR) system has been proposed that leverages a trusted edge computing layer that performs image encryption and feature extraction tasks, reducing the processing overload on user devices and bolstering system efficiency. Feature extraction harnesses the MobileNetV2 deep learning model, which enables the extraction of intricate visual features, enhancing image retrieval accuracy in the presence of high inter-class similarity in the dataset. Furthermore, the system has been deployed in a distributed storage environment, ensuring image availability even during server outages. The proposed system also incorporates trusted third-party auditing (TPA) as a means to verify the integrity of images during the storage and retrieval processes. The presence of TPA plays a crucial role in maintaining the reliability and trustworthiness of the stored images. The proposed system achieves a high mean Average Precision (mAP) of 0.889, surpassing existing PPCBIR systems. Overall, the system prioritizes image retrieval performance, privacy, availability, and integrity, making it suitable for processing remote sensing image data efficiently and securely.
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All publicly available datasets have been utilized for this work.
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Conceptualization: Vetriselvi V, Ajitesh M, Deekshith M, Arun Amaithi Rajan, Hemanth D;
Methodology and Development: Ajitesh M, Deekshith M, Hemanth D;
Formal analysis and investigation: Ajitesh M, Deekshith M, Hemanth D;
Writing - original draft preparation: Ajitesh M, Deekshith M, Arun Amaithi Rajan, Hemanth D;
Writing - review and editing: Deekshith M, Ajitesh M, Arun Amaithi Rajan, Vetriselvi V;
Supervision: Vetriselvi V.
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Communicated by: H. Babaie
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M, A., M, D., Amaithi Rajan, A. et al. EdgeShield: Attack resistant secure and privacy-aware remote sensing image retrieval system for military and geological applications using edge computing. Earth Sci Inform (2024). https://doi.org/10.1007/s12145-024-01256-z
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DOI: https://doi.org/10.1007/s12145-024-01256-z