Content-Based Secure Image Retrieval in an Untrusted Third-Party Environment
In this digital world, where availability of the image-generating tools is quite common and owing to the rapid growth of Internet knowledge, people use to exchange massive volume of images every day which results in creating large image repositories. So, retrieving appropriate image available on these repositories is one of the vital tasks. This problem leads to evolving content-based image retrieval (CBIR). As the generation of image increases, people start transferring these images to a remote third-party server, but these images may have personal information. This leads to adding privacy concerns toward the system as transferring personal data to some other place might be a cause of leakage of information or transfer to an unauthorized person. So, to keep this in mind, sensitive images like medical and personal images require encryption before being a contracted out for the privacy-preserving resolutions. In this work, we have deployed ACM for image encryption as well as asymmetric scalar product preserving encryption (ASPE) for feature vector encryption and similarity matching. We have demonstrated our results based on various benchmark databases.
History
Presented at
International Conference on Frontiers of Intelligent Computing: Theory and Applications. Evolution in Computational Intelligence. FICTA 2022, 18-19 June, Aizawl, IndiaPublisher
SpringerVersion
- AM (Accepted Manuscript)
Citation
Sengar, S.S., Kumar, S. (2023) Content-Based Secure Image Retrieval in an Untrusted Third-Party Environment. In: Bhateja, V., Yang, XS., Lin, J.CW., Das, R. (eds) Evolution in Computational Intelligence. FICTA 2022. Smart Innovation, Systems and Technologies, Vol 326. Springer, Singapore. https://doi.org/10.1007/978-981-19-7513-4_26Print ISSN
2190-3018Electronic ISSN
2190-3026ISBN
978-981-19-7513-4Cardiff Met Affiliation
- Cardiff School of Technologies
Cardiff Met Authors
Sandeep Singh SengarCopyright Holder
- © The Authors
Language
- en