本研究提出了新的增強多關鍵詞語義搜索（EA-MKSS）方式，用於保護隱私的加密數據搜索。保護隱私的搜索方法對於儲存在通常由第三方公司管理的雲服務器上的敏感或高度私密數據變得至關重要。雖然已經有多種搜索方法用於加密數據，但有些方案可能缺乏用戶搜索的靈活性，或忽視了語義效應。本研究提出的EA-MKSS方案專注於考慮關鍵詞之間的語義關係，並改進其精確度。用戶搜索請求是基於字典和查詢關鍵詞之間的相似性來制定的。設置閾值用於提高搜索精確度。秘密鑰匙加密被用來確保上傳數據的安全以及用戶查詢的隱私。使用真實世界數據集獲得的實驗結果證明，該方法返回了高精確度的搜索結果。所提出的EA-MKSS方案為保護隱私的加密數據語義搜索提供了一個有前景的解決方案，並可能在醫療保健，電子商務和雲計算等領域有潛在的應用。

This study proposes an Enhanced Multi-Keyword Semantic Search (EA-MKSS) scheme for privacy-preserving encrypted data searches. Privacy-preserving search methods have become critical for sensitive or highly private data stored on cloud servers typically managed by third-party companies. Although several search methods have been used for encrypted data, some schemes may need more flexibility in user searches or overlook the semantic effects. The EA-MKSS scheme proposed in this study focuses on considering semantic relationships between keywords and improving their precision. User search requests are formulated based on the similarity between the dictionary and query keywords. A set threshold is used to improve search precision. Secret key encryption ensures the uploaded data's security and user queries' privacy. The experimental results obtained using a real-world dataset demonstrated that the proposed method returned search results with high precision. The proposed EA-MKSS scheme provides a promising solution for privacy-preserving semantic searches of encrypted data, with potential applications in healthcare, e-commerce, and cloud computing.

[1] D. X. Song, D. Wagner, and A. Perrig, “Practical techniques for searches on encrypted data,” in 2012 IEEE Symposium on Security and Privacy, (Los Alamitos, CA, USA), pp. 44–55, IEEE Computer Society, may 2000.
[2] C. Wang, N. Cao, J. Li, K. Ren, and W. Lou, “Secure ranked keyword search over encrypted cloud data,” in 2010 IEEE 30th International Conference on Distributed Computing Systems, pp. 253–262, 2010.
[3] C. Wang, N. Cao, K. Ren, and W. Lou, “Enabling secure and efficient ranked keyword search over outsourced cloud data,” IEEE Transactions on Parallel and Distributed Systems, vol. 23, no. 8, pp. 1467–1479, 2011.
[4] N. Cao, C. Wang, M. Li, K. Ren, and W. Lou, “Privacy-preserving multi-keyword ranked search over encrypted cloud data,” IEEE Transactions on Parallel and Distributed Systems, vol. 25, no. 1, pp. 222–233, 2014.
[5] W. Sun, B. Wang, N. Cao, M. Li, W. Lou, Y. T. Hou, and H. Li, “Privacy-preserving multi-keyword text search in the cloud supporting similarity-based ranking,” in Proceedings of the 8th ACM SIGSAC Symposium on Information, Computer and Communications Security, ASIA CCS ’13, (New York, NY, USA), p. 71–82, Association for Computing Machinery, 2013.
[6] C. Orencik, M. Kantarcioglu, and E. Savas, “A practical and secure multi-keyword search method over encrypted cloud data,” in 2013 IEEE Sixth International Conference on Cloud Computing, pp. 390–397, IEEE Computer Society, 2013.
[7] S. Kamara, C. Papamanthou, and T. Roeder, “Dynamic searchable symmetric encryption,” in Proceedings of the 2012 ACM Conference on Computer and Communications Security, CCS ’12, (New York, NY, USA), p. 965–976, Association for Computing Machinery, 2012.
[8] S. Kamara and C. Papamanthou, “Parallel and dynamic searchable symmetric encryption,” in Financial Cryptography, vol. 7859 of Lecture Notes in Computer Science, pp. 258–274, Springer, Berlin, Heidelberg, 2013.
[9] Z. Xia, X. Wang, X. Sun, and Q. Wang, “A secure and dynamic multi-keyword ranked search scheme over encrypted cloud data,” IEEE Transactions on Parallel and Distributed Systems, vol. 27, no. 2, pp. 340–352, 2016.
[10] C. Guo, R. Zhuang, C.-C. Chang, and Q. Yuan, “Dynamic multi-keyword ranked search based on bloom filter over encrypted cloud data,” IEEE Access, vol. 7, pp. 35826–35837, 2019.
[11] J. Li, Q. Wang, C. Wang, N. Cao, K. Ren, and W. Lou, “Fuzzy keyword search over encrypted data in cloud computing,” in 2010 Proceedings IEEE INFOCOM, pp. 1–5, 2010.
[12] C. Wang, K. Ren, S. Yu, and K. M. R. Urs, “Achieving usable and privacy-assured similarity search over outsourced cloud data,” in 2012 Proceedings IEEE INFOCOM, pp. 451–459, IEEE, 2012.
[13] B. Wang, S. Yu, W. Lou, and Y. T. Hou, “Privacy-preserving multi-keyword fuzzy search over encrypted data in the cloud,” in IEEE INFOCOM 2014 - IEEE Conference on Computer Communications, pp. 2112–2120, IEEE, 2014.
[14] Z. Fu, X. Wu, C. Guan, X. Sun, and K. Ren, “Toward efficient multi-keyword fuzzy search over encrypted outsourced data with accuracy improvement,” IEEE Transactions on Information Forensics and Security, vol. 11, no. 12, pp. 2706–2716, 2016.
[15] Z. Li and H. Yao, “Dynamic multi-keyword ranked search based on simhash in cloud computing,” in 2019 IEEE 21st International Conference on High Performance Computing and Communications; IEEE 17th International Conference on Smart City; IEEE 5th International Conference on Data Science and Systems (HPCC/SmartCity/DSS), pp. 591–598, 2019.
[16] Z. Xia, Y. Zhu, X. Sun, and L. Chen, “Secure semantic expansion based search over encrypted cloud data supporting similarity ranking,” Journal of Cloud Computing, vol. 3, p. 8, 2014.
[17] Z. Fu, X. Sun, N. Linge, and L. Zhou, “Achieving effective cloud search services: multi-keyword ranked search over encrypted cloud data supporting synonym query,” IEEE Transactions on Consumer Electronics, vol. 60, no. 1, pp. 164–172, 2014.
[18] Z. Fu, F. Huang, X. Sun, A. V. Vasilakos, and C.-N. Yang, “Enabling semantic search based on conceptual graphs over encrypted outsourced data,” IEEE Transactions on Services Computing, vol. 12, no. 5, pp. 813–823, 2019.
[19] Z. Fu, F. Huang, K. Ren, J. Weng, and C. Wang, “Privacy-preserving smart semantic search based on conceptual graphs over encrypted outsourced data,” IEEE Transactions on Information Forensics and Security, vol. 12, no. 8, pp. 1874–1884, 2017.
[20] Z. Fu, L. Xia, X. Sun, A. X. Liu, and G. Xie, “Semantic-aware searching over encrypted data for cloud computing,” IEEE Transactions on Information Forensics and Security, vol. 13, no. 9, pp. 2359–2371, 2018.
[21] B. Lang, J. Wang, M. Li, and Y. Liu, “Semantic-based compound keyword search over encrypted cloud data,” IEEE Transactions on Services Computing, vol. 14, no. 3, pp. 850–863, 2021.
[22] X. Dai, H. Dai, G. Yang, X. Yi, and H. Huang, “An efficient and dynamic semantic-aware multikeyword ranked search scheme over encrypted cloud data,” IEEE Access, vol. 7, pp. 142855–142865, 2019.
[23] F.-J. Hsieh, T.-L. Chin, C.-Y. Huang, S.-H. Shen, and C.-A. Shen, “Semantic multi-keyword search over encrypted cloud data with privacy preservation,” in 2019 IEEE 90th Vehicular Technology Conference (VTC2019-Fall), pp. 1–5, IEEE, 2019.
[24] W. Yang and Y. Zhu, “A verifiable semantic searching scheme by optimal matching over encrypted data in public cloud,” IEEE Transactions on Information Forensics and Security, vol. 16, pp. 100–115, 2021.
[25] J. Li, J. Ma, Y. Miao, F. Yang, X. Liu, and K.-K. R. Choo, “Secure semantic-aware search over dynamic spatial data in vanets,” IEEE Transactions on Vehicular Technology, vol. 70, no. 9, pp. 8912–8925, 2021.
[26] X. Dai, H. Dai, C. Rong, G. Yang, F. Xiao, and B. Xiao, “Enhanced semantic-aware multi-keyword ranked search scheme over encrypted cloud data,” IEEE Transactions on Cloud Computing, vol. 10, no. 4, pp. 2595–2612, 2022.
[27] G. Salton, A. Wong, and C.-S. Yang, “A vector space model for automatic indexing,” Communications of the ACM, vol. 18, no. 11, pp. 613–620, 1975.
[28] T. Mikolov, K. Chen, G. Corrado, and J. Dean, “Efficient estimation of word representations in vector space,” arXiv preprint arXiv:1301.3781, 2013.
[29] W. K. Wong, D. W.-l. Cheung, B. Kao, and N. Mamoulis, “Secure knn computation on encrypted databases,” in Proceedings of the 2009 ACM SIGMOD International Conference on Management of data, pp. 139–152, 2009.
[30] K. Lang, “Newsweeder: Learning to filter netnews,” in Proceedings of the 12th International Conference on Machine Learning, pp. 331–339, Morgan Kaufmann publishers Inc.: San Mateo, CA, USA, 1995.
[31] Q. V. Le and T. Mikolov, “Distributed representations of sentences and documents,” in International conference on machine learning, pp. 1188–1196, PMLR, 2014.
[32] P. Jaccard, “Étude comparative de la distribution florale dans une portion des alpes et des jura,” Bulletin de la Societe Vaudoise des Sciences Naturelles, vol. 37, pp. 547–579, 1901.