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An Efficient Scheme for Secure Similarity-Based Medical Image Retrieval using Searchable Symmetric Encryption
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 186 - Number 22 |
| Year of Publication: 2024 |
| Authors: Irene Getzi S. |
10.5120/ijca2024923655
|
Irene Getzi S. . An Efficient Scheme for Secure Similarity-Based Medical Image Retrieval using Searchable Symmetric Encryption. International Journal of Computer Applications. 186, 22 ( May 2024), 19-24. DOI=10.5120/ijca2024923655
Abstract
The knowledge extracted from medical imaging data, amassed from hospital cloud repositories can transform the quality of healthcare. This research paper proposes a secure medical image retrieval scheme using Searchable Symmetric Encryption that performs similarity search over encrypted Chest X-Ray (CXR) dataset. The secure index is built using randomized Histogram of Oriented Gradients (HOG) feature descriptor and is organized as an N-dimensional dense array. The search phase uses a probabilistic token generation approach using the inner product of vectors to prevent statistical attacks and to control leakage. Similarity retrieval implemented using Lloyd’s algorithm with seed selection facilitate efficient search. The CXR image dataset of pneumonia affected patients from National Institute of Health, USA is used to test the efficacy of the scheme. The randomization used at various levels such as wavelet approximation, sparse randomized matrices and standardization of the feature vector diffuses the data and affects the reconstruction of the image. The AUC scores of 0.877 using ROC and 0.906 using precision-recall curves show that the secure retrieval accuracy is compatible with the non-secure algorithms. The experimental results and mathematical justification are reported.
References
- Song DX, Wagner D, Perrig A, “Practical techniques for searches on encrypted data”, In proceedings of 2000 IEEE Symposium on Security and Privacy, p. 44–55, 2000.
- Xia Z, Wang X, Sun X, Wang Q, “A Secure and Dynamic Multi-Keyword Ranked Search Scheme over Encrypted Cloud Data”, IEEE Transactions on Parallel Distributed Systems, Vol. 27(2), pp.340–352, 2016.
- Cash D, Jarecki S, Jutla C, Krawczyk H, Rosu MC, Steiner M, “Highly-scalable searchable symmetric encryption with support for Boolean queries”, In proceedings of Advances in Cryptology– CRYPTO 2013, Springer, pp. 353–373, 2013.
- Getzi I, Durairaj C. D, “A Dynamic Scheme for Secure Searches over Distributed Massive Datasets in Cloud Environment using Searchable Symmetric Encryption Technique”, International Journal of Information Security Science, Vol. 7(3), pp. 126–139, 2018.
- Cheng H, Zhang X, Yu J, “A Coefficient histogram-based retrieval for encrypted JPEG images”, Multimedia Tools and Applications, Vol. 75(21), pp. 13791–13803, 2016.
- Hsu CY, Lu CS, Pei SC, ‘Image feature extraction in encrypted domain with privacy-preserving SIFT”, IEEE Transactions on Image Processing, Vol. 21(11), 4593–4607, 2012.
- Yang T, Ma J, Wang Q, Miao Y, Wang X, Meng Q, “Image Feature Extraction in Encrypted Domain With Privacy Preserving Hahn Moments”, IEEE Access, Vol. 6(4), pp.47521– 47534, 2018.
- Erkin Z, Franz M, Guajardo J, Katzenbeisser S, Lagendijk I, Toft T, “Privacy-preserving face recognition”, In proceedings of International Symposium on Privacy Enhancing Technologies Symposium, Springer, pp. 235–253, 2009.
- Lu W, Varna AL, Swaminathan A, Wu M, “Secure image retrieval through feature protection”, In proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2009, pp. 1533–1536, 2009.
- Lu W, Swaminathan A, Varna AL, Wu M, “Enabling search over encrypted multimedia databases”, Media Forensics and Security, Vol. 7254, pp. 725418-725429.
- Xia Z, Xiong NN, Vasilakos AV, Sun X, “EPCBIR: An efficient and privacy-preserving content-based image retrieval scheme in cloud computing”, Information Sciences, Vol. 387, pp. 195–204, 2017.
- Wang Q, He M, Du M, Chow SS, Lai RW, Zou Q, “Searchable encryption over feature-rich data”, IEEE Transactions on Dependable and Secure Computing, Vol. 15(3), pp. 496– 510, 2018.
- Yan H, Chen Z, Jia C, “SSIR: Secure similarity image retrieval in IoT”, Information Sciences, Vol. 479, pp. 153–163, 2019.
- Yuan J, Yu S, Guo L. Seisa, “Secure and efficient encrypted image search with access control”, In proceedings of IEEE Conference on Computer Communications (INFOCOM), pp. 2083–2091, 2015.
- Liang H, Zhang X, Cheng H, Wei Q, “Secure and Efficient Image Retrieval over Encrypted Cloud Data”, Security and Communication Networks, Hindawi, Vol. 2018, Article ID 7915393, 2018.
- Yang M, Trifas M, Chen L, Song L, Aires D, Elston J, “Secure patient information and privacy in medical imaging” J Syst Cybern Inf. Vol. 8(3), pp. 63–66, 2010.
- Bellafqira R, Coatrieux G, Bouslimi D, Quellec G, “An end-to-end secure CBIR over encrypted medical database”, In proceedings of IEEE 38th Annual International Conference on Engineering in Medicine and Biology Society (EMBC), pp. 2537–2540, 2016.
- Xiaoming S, Ning Z, Haibin W, Xiaoyang Y, Xue W, Shuang Y, “Medical Image Retrieval Approach by Texture Features Fusion Based on Hausdorff Distance”, Mathematical Problems in Engineering. pp. 1–12, 2018.
- Johnson WB, Lindenstrauss J, “Extensions of Lipschitz mappings into a Hilbert space”, Contemporary mathematics, Vol. 26(1), pp. 189-206, 1984.
- Achlioptas D, “Database-friendly random projections: Johnson-Lindenstrauss with binary coins”, Journal of com-puter and System Sciences. Vol. 66(4), pp. 671–687, 2003.
- Getzi I, Durairaj C D, Raj J V, “Efficient Image Retrieval approach for Large-scale Chest X Ray data using Hand-Crafted Features and Machine Learning Algorithms”, International Journal of Computer Sciences and Engineering, Vol. 6(11), pp. 890–896, 2018.
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