Significance of Processing Queries and Implementation of Cipher in Remote Location

Mishra Suchismita¹, Mishra Bibhuti Bhusan^2, and Mishra Sambit Kumar³

¹Full Time Research Scholar, Siksha O Anusandhan University, Bhubaneswar

²Asst. Professor, Siksha O Anusandhan University, Bhubaneswar

³Professor & Head, Department of Computer Sc.& Engg., G.I.E.T., Bhubaneswar.

Cite this paper:
Mishra Suchismita, Mishra Bibhuti Bhusan and Mishra Sambit Kumar. Significance of Processing Queries and Implementation of Cipher in Remote Location. Journal of Computer Sciences and Applications. 2015; 3(6):127-129. doi: 10.12691/jcsa-3-6-3

Abstract

Confidentiality, Integrity and Availability are the three key attributes in preserving the essence of the data being used in remote exchanges between users & servers. Always there is need of maintaining a balance between the access and the protection of the system dealing with data. The encryption concept also proved as a powerful tool helps in enhancing the integrity of the remote data. The database server, clients and high speed Internet services are very much essential for processing data as well as optimizing queries in remote locations. Therefore security measures must be taken care, while processing private queries. It has been observed that cloud computing plays a vital role of preserving queries while processing and maintaining the privacy of data. In this paper, it is primarily focused regarding the security measures of data while processing queries in remote locations where the position of database server is not known and implementation of cipher in data transfer.

Keywords:
cipher cloud computing data abstraction generalization encryption query term

This work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

References:

[1]	TingjianGe, Stanley B. Zdonik, and Stanley B. Zdonik. Answering aggregation queries in a secure system model. In VLDB, pages 519-530, 2007.
[2]	Guo, Yubin, et al. “A solution for privacy- preserving data manipulation and query on nosql database.” Journal of Computers 8.6 (2013): 1427-1432.
[3]	Jerry Kiernan, RakeshAgrawal, RamakrishnanSrikant, and YirongXu. Order preserving encryption for numeric data. In Proceedings of the 2004 ACM SIGMOD international conference on Management of data, SIGMOD’ 04, pages 563-574, New York, NY, USA, 2004. ACM.
[4]	Hu, Haibo, “Processing private queries over untrusted data cloud through privacy homomorphism.” Data Engineering (ICDE), 2011 IEEE 27th International Conference on. IEEE, 2011.
[5]	Kilzer, Ann, Emmett Witchel, Indrajit Roy, Vitaly Shmatikov, and Srinath T.V. Setty. “Airavat: Security and Privacy for Map Reduce.”
[6]	Kraft, D.H., Bordogna, G., and Pasi, G.: Fuzzy Set Techniques in Information Retrieval, in Bezdek, J.C., Didier, D. and Prade, H. (eds.), Fuzzy Sets in Approximate Reasoning and Information Systems, vol. 3, The Handbook of Fuzzy Sets Series, Norwell, MA: Kluwer Academic Publishers, 1999.
[7]	Feig M, Abdullah M, Johnsson L, Pettitt BM (1999) Large scale distributed data repository: design of a molecular dynamics trajectory database. Future Generation Computer Syst16 (1):101-110.
[8]	Chapman A, Jagadish HV, Ramanan P (2008) efficient provenance storage. In: SIGMOD Conference. ACM, Vancouver, BC, Canada. pp 993-1006.
[9]	Amazon Elastic Compute Cloud (EC2): http://www.amazon.com/gp/browse.html? Node=201590011, accessed Dec 2008.