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IJSTR >> Volume 9 - Issue 1, January 2020 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



Cloud Data Security Using Group Multi-Keyword Top K Similarity Search Using Asymmetric Encryption

[Full Text]

 

AUTHOR(S)

Ms. Khuspreet Kaur, Dr. Meenakshi Bansal

 

KEYWORDS

Group multi-keyword search, Asymmetric SE scheme, Cloud computing, Data encryption, random traversal, multi-keyword top-k search.

 

ABSTRACT

Cloud computing is a kind of area which has opened new doors to everyone.This allows for new types of services where online computing and network resources are available. Anyone who want to use it can pay and use online service. One of cloud computing most popular services is data outsourcing. Both public and private organizations can now outsource their large amounts of data to the cloud for cost and convenience reasons and enjoy the benefits of remote storage and management. At the same time, a major concern is the confidentiality of data stored remotely on untrusted cloud servers. To reduce these concerns about sensitive data such as personal health records, emails, income tax and financial reports, which are usually outsourced using well-known cryptographic techniques in encrypted form. Although encrypted data storage protects remote data from unauthorized access, it obscures some basic but essential data use services such as searching for plaintext keywords. For the encrypted data used by AWS and Google Cloud, a lot of techniques are used. Like Searchable encryption, you can store encrypted documents on a remote, honest but curious server, and query that data on the server itself without having to decrypt documents before searching. Not only does this protect the data from the server's prying eyes, but it can also reduce the overhead communication between the server and the user and the latter's local processing.

 

REFERENCES

[1] Song, D. X., Wagner, D., &Perrig, A. (2000). Practical techniques for searches on encrypted data. In Proceeding 2000 IEEE Symposium on Security and Privacy. S&P 2000(pp. 44-55). IEEE.
[2] Seth, S. M., & Mishra, R. (2011). Comparative analysis of encryption algorithms for data communication 1.
[3] Agrawal, M., & Mishra, P. (2012). A comparative survey on symmetric key encryption techniques. International Journal on Computer Science and Engineering, 4(5), 877.
[4] Mondal, B., Dasgupta, K., & Dutta, P. (2012). Load balancing in cloud computing using stochastic hill climbing-a soft computing approach. Procedia Technology, 4, 783-789.
[5] Liang, H., Cai, L. X., Huang, D., Shen, X., & Peng, D. (2012). An SMDP-based service model for inter-domain resource allocation in mobile cloud networks. IEEE transactions on vehicular technology, 61(5), 2222-2232.
[6] Orencik, C., Kantarcioglu, M., &Savas, E. (2013, June). 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.
[7] Mahmoud, M. M., & Shen, X. (2012). A cloud-based scheme for protecting source-location privacy against hotspot-locating attack in wireless sensor networks. IEEE Transactions on Parallel and Distributed Systems, 23(10), 1805-1818.
[8] Cao, N., Wang, C., Li, M., Ren, K., & Lou, W. (2013). Privacy-preserving multi-keyword ranked search over encrypted cloud data. IEEE Transactions on parallel and distributed systems, 25(1), 222-233.
[9] Jung, T., Mao, X., Li, X. Y., Tang, S. J., Gong, W., & Zhang, L. (2013, April). Privacy-preserving data aggregation without secure channel: Multivariate polynomial evaluation. In 2013 Proceedings IEEE INFOCOM (pp. 2634-2642). IEEE.
[10] Yang, Y., Li, H., Liu, W., Yao, H., & Wen, M. (2014, December). Secure dynamic searchable symmetric encryption with constant document update cost. In 2014 IEEE Global Communications Conference (pp. 775-780). IEEE.
[11] Tayde, S., &Siledar, S. (2015). File Encryption, Decryption Using AES Algorithm in Android Phone. International Journel of Advanced Research in computer science and software engineering, 5(5).
[12] Saini, N., Pandey, N., & Singh, A. P. (2015, September). Enhancement of security using cryptographic techniques. In 2015 4th International Conference on Reliability, Infocom Technologies and Optimization (ICRITO)(Trends and Future Directions) (pp. 1-5). IEEE.
[13] K SrinivasaRao ,Dr Y. Vamsidhar(2015). Privacy-preserving multi-keyword ranked search over encrypted cloud data.International Journal of Applied Sciences, Engineering and Management ISSN 2320 – 3439(4),51 – 56.
[14] Tang, J., Cui, Y., Li, Q., Ren, K., Liu, J., &Buyya, R. (2016). Ensuring security and privacy preservation for cloud data services. ACM Computing Surveys (CSUR), 49(1), 13.
[15] Ying, Z., Li, H., Ma, J., Zhang, J., & Cui, J. (2016). Adaptively secure ciphertext-policy attribute-based encryption with dynamic policy updating. Science China Information Sciences, 59(4), 042701.
[16] Ding, X., Liu, P., & Jin, H. (2017). Privacy-Preserving Multi-Keyword Top-$ k $ k Similarity Search Over Encrypted Data. IEEE Transactions on Dependable and Secure Computing, 16(2), 344-357.
[17] Liu, C., Zhu, L., & Chen, J. (2017). Efficient searchable symmetric encryption for storing multiple source dynamic social data on cloud. Journal of Network and Computer Applications, 86, 3-14.
[18] Kisembe, P., &Jeberson, W. (2017). Future of Peer-To-Peer Technology with the rise of Cloud Computing. International Journal of Peer to Peer Networks (IJP2P), 8.
[19] Peng, T., Lin, Y., Yao, X., & Zhang, W. (2018). An efficient ranked multi-keyword search for multiple data owners over encrypted cloud data. IEEE Access, 6, 21924-21933.
[20] Ian H. Witten, Alistair Moffat, and Timothy C. Bell: Managing Gigabytes (2nd Ed.): Compressing and Indexing Documents and Images. Morgan Kaufmann Publishers Inc., 1999.
[21] ZvikaBrakerski: Fully homomorphic encryption without modulus switching from classical GapSVP. In Proceeding of the 32nd Annual International Cryptology Conference CRYPTO 2012, 2012.
[22] ZvikaBrakerski, Craig Gentry, and Vinod Vaikuntanathan: (Leveled) Fully homomorphic encryption without bootstrapping. In Proceedings of the 3rd Innovations in Theoretical Computer Science Conference, 2012.
[23] ZvikaBrakerski, Craig Gentry, and Vinod Vaikuntanathan: Fully Homomorphic Encryption without Bootstrapping. Cryptology ePrint Archive, Report 2011/277, 2011.
[24] Yan-Cheng Chang and Michael Mitzenmacher: Privacy preserving keyword searches on remote encrypted data. In Proceedings of the 3rd International Conference on Applied Cryptography and Network Security, 2005.
[25] AshwinSwaminathan, Yinian Mao, Guan-Ming Su, Hongmei Gou, Avinash L. Varna, Shan He, Min Wu, and Douglas W. Oard: Confidentiality-preserving rank-ordered search. In Proceedings of the ACM Workshop on Storage Security and Survivability, 2007.
[26] RFC: Request for comments database. http://www.ietf.org/rfc.html, 2015.
[27] Bradford Nichols, Dick Buttlar, and Jacqueline Proulx Farrell: Pthreads programming. O’Reilly & Associates, Inc., 1996.
[28] Christoph Bösch, Pieter Hartel, Willem Jonker, and Andreas Peter: A survey of provably secure searchable encryption. ACM Computing Surveys, vol. 47, no. 2, pp. 1-51, 2014.
[29] Amos Fiat and Moni Naor: Broadcast encryption. In Proceedings of the 13th Annual International Cryptology Conference CRYPTO 1993, 1993.
[30] Dan Boneh and Mark Zhandry: Multiparty key exchange, efficient traitor tracing, and more from indistinguishability obfuscation. In Proceedings of the 34th Annual International Cryptology Conference CRYPTO 2014, 2014.
[31] Mark Zhandry: How to Avoid Obfuscation Using Witness PRFs. In Proceedings of the 13th IACR Theory of Cryptography Conference TCC 2016, 2016.
[32] Dan Boneh, Craig Gentry, and Brent Waters: Collusion resistant broadcast encryption with short ciphertexts and private keys. In Proceedings of the 25th Annual International Cryptology Conference CRYPTO 2005, 2005.
[33] Ryuichi Sakai and Jun Furukawa: Identity-based broadcast encryption. Cryptology ePrint Archive, Report 2007/217, 2007. [47] Cecile Delerablee, Pascal Paillier, and David Pointcheval: Fully collusion secure dynamic broadcast encryption with constant-size ciphertexts or decryption keys. In Proceedings of the First International Conference on Pairing-based Cryptography, 2007.
[34] B. Wang, S. Yu, W. Lou, and Y. T. Hou, “Privacy preserving multi-keyword fuzzy search over encrypted data in the cloud,” in INFOCOM, 2014 Proceedings IEEE, 2014, pp. 2112–2120.
[35] 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, ser. ASIA CCS ’13. ACM, 2013, pp. 71–82.
[36] C. Wang, K. Ren, S. Yu, and K. M. R. Urs, “Achieving usable and privacy-assured similarity search over outsourced cloud data,” in INFOCOM, 2012 Proceedings IEEE, 2012, pp. 451–459.
[37] A.Swaminathan, Y. Mao, G. M. Su, H. Gou, A. Varna, S. He, M. Wu, and D. Oard, “Confidentialitypreserving rank-ordered search,” in Proc. ACM ACM Workshop Storage Security Survivability, Alexandria, VA, 2007, pp. 7–12.
[38] C. Wang, N. Cao, K. Ren, and W. J. Lou, “Enabling secure and efficient ranked keyword search over outsourced cloud data,” IEEE Trans. Parallel Distrib. Syst., vol. 23, no. 8, pp. 1467–1479, Aug. 2012.
[39] D. X. D. Song, D. Wagner, and A. Perrig, “Practical techniques for searches on encrypted data,” in Proc. IEEE Symp. Security Priv., BERKELEY, CA, 2000, pp. 44–55.
[40] A.Selvanayagi, “Optimizing cloud gaming experience through map reducing”, in Scopus, vol.118, No.18, pp.2621-2626, Feb.2018.
[41] S.Saravanan, R.Bharathi, “Enhanced privacy and usability multikeyword search scheme Over mobile cloud storage”, in Scopus, vol.118, No.8, pp.2265- 2272, Feb. 2018.
[42] M.Murugesan, “Secure data compression scheme in cloud environments with backup recovery scheme”, in Scopus, vol.118, No.8, pp. 467-471, Feb. 2018
[43] S.P.Yazhini, S.Santhiya, “Reliability and Confidentiality based data storage in cloud using merkle hash tree technique”, in Scopus, vol. 118, No.8, pp.793-797, Feb. 2018.
[44] E. Shen, E. Shi, and B. Waters, “Predicate privacy in encryption systems,” in Theory of Cryptography. Springer, 2009, pp. 457–473.
[45] 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, ser. ASIA CCS ’13. ACM, 2013, pp. 71–82.
[46] 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.
[47] 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.
[48] C. D. Manning, P. Raghavan, H. Schutze ¨ et al., Introduction to information retrieval. Cambridge university press Cambridge, 2008, vol. 1, no. 1.
[49] S. Brin and L. Page, “The anatomy of a large-scale hypertextual web search engine,” Computer Networks and ISDN Systems, vol. 30, no. 17, 1998.
[50] J. Baek, R. Safavi-Naini, and W. Susilo, “Public key encryption with keyword search revisited,” in Computational Science and Its Applications. Springer, 2008, pp. 1249–1259.
[51] D. J. Park, K. Kim, and P. J. Lee, “Public key encryption with conjunctive field keyword search,” in Information security applications. Springer, 2004, pp. 73–86.
[52] W. M. Liu, L. Wang, P. Cheng, K. Ren, S. Zhu, and M. Debbabi, “Pptp: Privacy-preserving traffic padding in web-based applications,” IEEE Transactions on Dependable and Secure Computing, vol. 11, no. 6, Nov 2014.
[53] J. Li, Q. Wang, C. Wang, N. Cao, K. Ren, and W. Lou, “Fuzzy keyword search over encrypted data in cloud computing,” in INFOCOM, 2010 Proceedings IEEE, 2010, pp. 1–5.
[54] C. Wang, N. Cao, J. Li, K. Ren, and W. Lou, “Secure ranked keyword search over encrypted cloud data,” in Distributed Computing Systems (ICDCS), IEEE 30th International Conference on, 2010, pp. 253–262.
[55] C. Wang, K. Ren, S. Yu, and K. M. R. Urs, “Achieving usable and privacy-assured similarity search over outsourced cloud data,” in INFOCOM, 2012 Proceedings IEEE, 2012, pp. 451–459.
[56] M. Chuah and W. Hu, “Privacy-aware bedtree based solution for fuzzy multi-keyword search over encrypted data,” in Distributed Computing Systems Workshops (ICDCSW), the 31st International Conference on, 2011, pp. 273–281.
[57] B. Wang, S. Yu, W. Lou, and Y. T. Hou, “Privacy-preserving multi-keyword fuzzy search over encrypted data in the cloud,” in INFOCOM, 2014 Proceedings IEEE, 2014, pp. 2112–2120.
[58] M. Kuzu, M. S. Islam, and M. Kantarcioglu, “Efficient similarity search over encrypted data,” in Data Engineering (ICDE), 2012 IEEE 28th International Conference on, 2012, pp. 1156–1167.
[59] Q. Lv, W. Josephson, Z. Wang, M. Charikar, and K. Li, “Multiprobelsh: Efficient indexing for high-dimensional similarity search,” in Proceedings of the 33rd International Conference on Very Large Data Bases. VLDB Endowment, 2007, pp. 950–961. X. Yuan, H. Cui, [60] X. Wang, and C. Wang, “Enabling privacyassured similarity retrieval over millions of encrypted records,” in European Symposium on Research in Computer Security. Springer, 2015, pp. 40–60.