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                        "url": "https://www.jst.org.in/index.php/pub/article/download/747/673",
                        "purpose": "text-mining",
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                        "url": "https://www.jst.org.in/index.php/pub/article/download/747/1775",
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                "abstract": {
                    "value": "Data may be stored on a cloud and accessible from anywhere using mobile devices thanks to mobile cloud storage (MCS). MCS services are provided for commercial use by sizable firms like Apple I Cloud, Dropbox, Microsoft One Drive, and Google Drive. Since customers may not fully trust clouds, data security may be achieved using encryption techniques. However, sensitive data, including location data, is frequently included in location-based apps. This exposed data can be used to deduce the client's behavior and encrypted data. For instance, 80% of search queries may be recognized by a searchable encryption system using a generic inference attack with access pattern leaking and little prior knowledge. The activity of the client can also be inferred via oblivious technologies, such as oblivious transfer and oblivious storage.This study presents a mobile cloud storage system that simultaneously safeguards data confidentiality and privacy while being effective, secure, and privacy-preserving. An oblivious selection and update (OSU) protocol built on onion additive homo morphic encryption with constant encryption layers serves as the underlying primitive. This dramatically lowers computation and transmission costs by enabling clients to covertly retrieve encrypted data items from the cloud and update them with new information. The suggested approach is more appropriate for MCS situations because it has beneficial characteristics such a fine-grained data structure, minimal client-side processing, and constant communication overhead. The \"verification chunks\" technique also confirms that the strategy is resistant to malicious cloud assaults. According to the comparison and assessment, the suggested plan is more effective than currently available oblivious storage options in terms of client .A valuable tool for distant storage, akin to cloud storage, is remote data integrity checking.",
                    "lang": "en"
                },
                "license": {
                    "url": "https://creativecommons.org/licenses/by/4.0",
                    "start": "2023-08-07",
                    "applies_to": "vor"
                },
                "references": [
                    {
                        "key": "ref1",
                        "doi": "10.1007/s10207-014-0263-8",
                        "unstructured": "Yu, Y., Au, M.H., Mu, Y. et al. Enhanced privacy of a remote data integrity-checking protocol for secure cloud storage. Int. J. Inf. Secur. 14, 307–318(2015). https://doi.org/10.1007/s10207- 014-0263-8"
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                    {
                        "key": "ref2",
                        "doi": "10.1155/2014/820391",
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                    {
                        "key": "ref3",
                        "doi": "10.1109/access.2022.3211391",
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                    {
                        "key": "ref4",
                        "doi": "10.1109/access.2022.3198099",
                        "unstructured": "A. Goldstein, L. Fink and G. Ravid, “A Cloud-Based Framework for Agricultural Data Integration: A Top-Down-Bottom-Up Approach,” in IEEE Access, vol. 10, pp. 88527-88537, 2022, doi: 10.1109/ACCESS.2022.3198099"
                    },
                    {
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                        "unstructured": "Xiuguang Li, Ruifeng Li, Xu An Wang, Ke Niu, Hui Li, Xiaoyuan Yang, “Improved Efficient Privacy-Preserving Certificateless Provable Data Possession Scheme for Cloud Storage”, Security and Communication Networks, vol. 2022, Article ID 7302767, 9 pages,2022.https:// doi.org/10.1155/2022/7302767"
                    },
                    {
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                    },
                    {
                        "key": "ref7",
                        "doi": "10.1109/access.2020.3009539",
                        "unstructured": "X. Yang, M. Wang, T. Li, R. Liu and C. Wang, “Privacy-Preserving Cloud Auditing for Multiple Users Scheme With Authorization and Traceability,” in IEEE Access, vol. 8, pp. 130866-130877,2020,doi:10.1109/ ACCESS.2020.3009539"
                    },
                    {
                        "key": "ref8",
                        "doi": "10.1155/2017/4603237",
                        "unstructured": "Tengfei Tu, Lu Rao, Hua Zhang, Qiaoyan Wen, Jia Xiao, “Privacy-Preserving Outsourced Auditing Scheme for Dynamic Data Storage in Cloud”, Security and Communication Networks, vol. 2017, Article ID 4603237, 17 pages, 2017. https://doi.org/10.1155/2017/4603237"
                    },
                    {
                        "key": "ref9",
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                    },
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                        "key": "ref10",
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