We apologize for a recent technical issue with our email system, which temporarily affected account activations. Accounts have now been activated. Authors may proceed with paper submissions. PhDFocusTM
CFP last date
20 November 2024
Call for Paper
December Edition
IJCA solicits high quality original research papers for the upcoming December edition of the journal. The last date of research paper submission is 20 November 2024

Submit your paper
Know more
Reseach Article

Design and Implementation of Database Intrusion Detection System for Security in Database

by Udai Pratap Rao, Dhiren R. Patel
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 35 - Number 9
Year of Publication: 2011
Authors: Udai Pratap Rao, Dhiren R. Patel
10.5120/4431-6170

Udai Pratap Rao, Dhiren R. Patel . Design and Implementation of Database Intrusion Detection System for Security in Database. International Journal of Computer Applications. 35, 9 ( December 2011), 32-40. DOI=10.5120/4431-6170

@article{ 10.5120/4431-6170,
author = { Udai Pratap Rao, Dhiren R. Patel },
title = { Design and Implementation of Database Intrusion Detection System for Security in Database },
journal = { International Journal of Computer Applications },
issue_date = { December 2011 },
volume = { 35 },
number = { 9 },
month = { December },
year = { 2011 },
issn = { 0975-8887 },
pages = { 32-40 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume35/number9/4431-6170/ },
doi = { 10.5120/4431-6170 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:21:33.390312+05:30
%A Udai Pratap Rao
%A Dhiren R. Patel
%T Design and Implementation of Database Intrusion Detection System for Security in Database
%J International Journal of Computer Applications
%@ 0975-8887
%V 35
%N 9
%P 32-40
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, we propose database intrusion detection mechanism to enhance the security of DBMS. In a typical database environment, it is possible to define the profile of transactions that each user is allowed to execute. In our approach, we use the transactions profile and overall system architecture is divided into two parts, learning phase and intrusion detection phase. The learning phase generates authorized transactions profile automatically and is used at detection phase to check the behaviour of executable transactions. We also implement the detection phase with the help of Counting Bloom Filter (CBF) and comparing both the approaches.

References
  1. Fonseca, Vieira, M., Madeira, H, “Integrated intrusion detection in database,” In Bondavalli, A., Brasileiro, F, Rajsbaum S.(eds), LADC 2007. LNCS, vol 4746, pp 198-211. Springer, Heidelberg , 2007.
  2. Jinfu Chen, Yasheng Lu, and Xiaodong Xie, “An Auto-generating Approach of Transactions Profile Graph in Detection of Malicious Transaction” , in Proceedings of Third International Conference on International Information Hiding and Multimedia Signal Processing, pp. 562-565, IEEE, 2007.
  3. E. Bertino, S. Jajodia, and P. Samarati, “Database security:Research and practice”, Information Systems Journal, Volume 20, Number 7, 1995.
  4. Jose Fonseca, Marco Vieira, “Monitoring Database Application Behaviour for Intrusion Detection”, PRDC ’06 , pp. 383- 386, IEEE 2006.
  5. Jose Fonseca, Marco Vieira, and Henrique Madeira, “Detecting Malicious SQL” , C.lambrinoudakis, G.Pernul, A M. Tjoa(Eds.): Trusbus 2007, LNCS 4657, pp. 259-268, Springer Heidelberg, 2007.
  6. C. Y. chung, M. Gertz, K. Levitt, “DEMIDS: A Misuse Detection System for Database systems”, IFIP TC-11 WG 11.5 Conference on integrity and internal control in information system, PP. 159-178, 1999.
  7. V. C. S. Lee, J.A. Stankovic, S. H. Son, “intrusion detection in real-time database system Via time signatures”, real time technology and application symposium, PP. 124, 2000.
  8. Wenhui S., Tan T., “A novel intrusion detection system model for securing web based database systems”, In Proceedings of the 25th annual international computer software and application conference (COMPSAC), pp. 249-254, 2001.
  9. Y. Hu, B. Panda, “A data mining approach for database intrusion detection”, In Proceedings of the ACM Symposium on applied computing, pp. 711-716, 2004.
  10. Srivastava, A., Sural, S., Majumdar, A. K., “Weighted intra-transactions rule mining for database intrusion detection”, In Proceedings of the Pacific-Asia knowledge discovery and data mining (PAKDD), lecture notes in artificial intelligence, Springer. Pp. 611-620, 2006.
  11. Zhong Y., Qin X., “Database intrusion detection based on user query frequent itemsets mining with constraints”, In Proceeding of the 3rd international conference on information security, pp. 224-225, 2004.
  12. Bertino E., Terzi E., Kamra A., Vakali A., “Intrusion Detection in RBAC-Administered Database”, In Proceeding of the 21st annual computer security application conference (ACSAC), pp. 170-182, 2005.
  13. Udai Pratap Rao, G. J. Sahani, Dhiren R. Patel, “Detection of Malicious Activity in Role Based Access Control (RBAC) Enabled Databases”, International Journal of Information Assurance and Security, pp. 611-617, Volume 5, Issue 6, USA, ISSN 1554-1010,2010.
  14. Lee S.Y., Low W.L, Teoh P., “DIDAFIT: Detecting Intrusions in Database Through Fingerprinting Transactions”, in proceedings of the 4th International Conference on Enterprise Information system(ICEIS) 2002, pp. 121-128.
  15. Marco Vieira, Henrique Madeira, “Detection of Malicious Transactions in DBMS”, Dependable Computing, 2005. Proceedings. 11th Pacific Rim International Symposium on 12-14 Dec. 2005.
  16. Flavio Bonomi, Michael Mitzenmacher, Rina Panigrahy, Sushil Singh and George Varghese1, “An Improved Construction for Counting Bloom Filters” , ESA 2006, LNCS 4168, pp. 684–695, 2006.
Index Terms

Computer Science
Information Sciences

Keywords

Database Security Database Auditing Transaction Profile Counting Bloom Filter (CBF)