CFP last date
20 December 2024
Reseach Article

Review on QoS and Security of Database System using Genetic Algorithm

by Arun Kumar, Roop Lal, Gurpreet Singh
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 163 - Number 3
Year of Publication: 2017
Authors: Arun Kumar, Roop Lal, Gurpreet Singh
10.5120/ijca2017913481

Arun Kumar, Roop Lal, Gurpreet Singh . Review on QoS and Security of Database System using Genetic Algorithm. International Journal of Computer Applications. 163, 3 ( Apr 2017), 8-11. DOI=10.5120/ijca2017913481

@article{ 10.5120/ijca2017913481,
author = { Arun Kumar, Roop Lal, Gurpreet Singh },
title = { Review on QoS and Security of Database System using Genetic Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { Apr 2017 },
volume = { 163 },
number = { 3 },
month = { Apr },
year = { 2017 },
issn = { 0975-8887 },
pages = { 8-11 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume163/number3/27373-2017913481/ },
doi = { 10.5120/ijca2017913481 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:09:07.660142+05:30
%A Arun Kumar
%A Roop Lal
%A Gurpreet Singh
%T Review on QoS and Security of Database System using Genetic Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 163
%N 3
%P 8-11
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Both network security and quality of service (QoS) used up computational reference connected with IT procedure thereby could unsurprisingly influence the application form services. When it comes to confined computational reference, it is essential to type your communal impact concerning multi-level protection as well as QoS, which may be concurrently run optimization procedures to be able to give you a greater operation underneath the disposable computational resource. In this review has shown that the Genetic algorithm and Pareto-optimal security policies not only meet the security requirement of the user, but also provide the optimal QoS under the available computational resource. The overall objective of this paper is to analyze QoS and security of database system using Genetic algorithm.

References
  1. Xuancai Zhao, Qiuzhen Lin, Jianyong Chen, Xiaomin Wang, Jianping Yu, Zhong Ming, Optimizing security and quality of service in a Real-time database system using Multi-objective genetic algorithm, Expert Systems with Applications, Volume 64, 1 December 2016, Pages 11-23.
  2. Tao Xiang, Xiaoguo Li, Fei Chen, Shangwei Guo, Yuanyuan Yang, Processing secure, verifiable and efficient SQL over outsourced database, Information Sciences, Volume 348, 20 June 2016, Pages 163-178.
  3. Hababeh, I., Khalil, I., & Khreishah, A. (2015). Designing high performance we- b-based computing services to promote telemedicine database management system. IEEE Transactions on Services Computing, 8 (1), 47–64.
  4. Peter Frühwirt, Peter Kieseberg, Katharina Krombholz, Edgar Weippl, towards a forensic-aware database solution: Using a secured database replication protocol and transaction management for digital investigations, Digital Investigation, Volume 11, Issue 4, December 2014, Pages 336-348.
  5. Kashif, K., Madjid, M., Shi, Q., & Sohail, A. (2013). Component-based security system (COMSEC) with QoS for wireless sensor networks. Security and Communication Networks, 6 (4), 461–472.
  6. Al-Sayid, N., & Aldlaeen, D. (2013). Database security threats: A survey study. In 2013 5th International conference on computer science and information technology (CSIT) (pp. 60–64).
  7. Alomari, F., & Menasce, D. (2013). Self-protecting and self-optimizing database sys- tems: Implementation and experimental evaluation. In Proceedings of the 2013 ACM cloud and autonomic computing conference, Article No. 18.
  8. Alomari, F., & Menasce, D. (2012). An autonomic framework for integrating security and quality of service support in databases. In 2012 IEEE sixth international conference on software security and reliability (SERE) (pp. 51–60).
  9. Woochul, K., Son, S., & Stankovic, J. (2012). Design, implementation, and evaluation of a QoS-aware real-time embedded database. IEEE Transactions on Computers, 61 (1), 45–49.
  10. Martins, F., Carrano, E., Wanner, E., Takahashi, R. , & Mateus, G. (2011). A hybrid multiobjective evolutionary approach for improving the performance of wire- less sensor networks. IEEE Sensors Journal, 11 (3), 545–554.
  11. Taneja, N., Raman, B., & Gupta, I. (2011). Chaos based partial encryption of spit compressed images. International Journal of Wavelets Multiresolution and Infor- mation Processing, 9 (2), 317–331.
  12. Huang, B., Buckley, B., & Kechadi, T. (2010). Multi-objective feature selection by using NSGA-II for customer churn prediction in telecommunications. Expert Systems with Applications, 37 (5), 3638–3646.
  13. Kamra, A., & Bertino, E. (2009). Survey of machine learning methods for database security. In Machine learning in cyber trust (pp. 53–71). Springer.
  14. Jabbour, G., & Menasee, D. (2008). Policy-based enforcement of database security configuration through autonomic capabilities. In International conference on au- tonomic and autonomous systems (pp. 188–197).
  15. Kang, K., Oh, J. , & Son, S. (2007a). Chronos: Feedback control of a real database sys- tem performance. In Proceedings 28th IEEE international conference on real-time systems symposium (RTSS) (pp. 267–276).
  16. Amirijoo, M., Hansson, J., & Son, S. (2006). Specification and management of QoS in real-time databases supporting imprecise computations. IEEE Transactions on Computers, 55 (3), 304–319.
  17. Eduardo Fernández-Medina, Mario Piattini, Designing secure databases, Information and Software Technology, Volume 47, Issue 7, 15 May 2005, Pages 463-477.
Index Terms

Computer Science
Information Sciences

Keywords

Database Network Security Quality of Service Database System Genetic Algorithm