When considering Intrusion Detection and the Insider Threat, most researchers tend to focus on the network architecture rather than the database which is the primary target of data theft. It is understood that the network level is adequate for many intrusions where entry into the system is being sought however it is grossly inadequate when considering the database and the authorized insider. Recent writings suggest that there have been many attempts to address the insider threat phenomena in regards to database technologies by the utilization of detection methodologies, policy management systems and behavior analysis methods however, there appears to be a lacking in the development of adequate solutions that will achieve the level of detection that is required. While it is true that Authorization is the cornerstone to the security of the database implementation, authorization alone is not enough to prevent the authorized entity from initiating malicious activities in regards to the data stored within the database. Behavior of the authorized entity must also be considered along with current data access control policies. Each of the previously mentioned approaches to intrusion detection at the database level has been considered individually, however, there has been limited research in producing a multileveled approach to achieve a robust solution. The research presented outlines the development of a detection framework by introducing a process that is to be implemented in conjunction with information requests. By utilizing this approach, an effective and robust methodology has been achieved that can be used to determine the probability of an intrusion by the authorized entity, which ultimately address the insider threat phenomena at its most basic level.
 S. Gaudin, (2007, July, 23). “Computer Crimes Charged in College Cash-for-Grades Scheme, 2007. http://www.informationweek.com/story/showArticle.jhtml?a
 J. Vijayan, “DBA Admits to Theft of 8.5m Records,” 2007. http://www.computerworld.com/action/article.do?command=viewArticleBasic&articleId=308611&source=rss_topic82
 E. Shmueli, R. Vaisenberg, Y. Elovici and C. Glezer, “Database Encryption: An Overview of Contemporary Challenges and Design Considerations”, ACM SIGMOD Record, Vol. 38 No. 3, 2009, pp. 29-34. doi:10.1145/1815933.1815940
 H. Debar, M. Becke and D. Siboni, “A Neural Network Component for an Intrusion Detection System,” Proceedings of IEEE Computer Society Symposium on Security and Privacy, Oakland, 4-6 May 1992, pp. 240-250.
 T. F Lunt, A. Tamru, F.Gilham, R. Jagannathan, C. Jalai, P. G. Newman, H. S. Javitz, A. Valdes and T. D. Garvey, “A Real-time Intrusion Detection Expert System (IDES)”, Final Technical Report for SRI Project 6784, 1992.
 R. A. Kemmerer and P.A. Porras, “State Transition Analysis: A Rule-based Intrusion Detection Approach,” IEEE Transactions on Software Engineering, Vol. 21 No. 3, 1995, pp. 181-199. doi:10.1109/32.372146
 X. An, D. Jutla and N. Cercone, “A Bayesian Network Approach to Detecting Privacy Intrusion,” Proceedings of 2006 International Conferences on Web Intelligence and Intelligent Agent Technology Workshop, Hongkong, 18-22 December 2006, pp. 73-76. doi:10.1109/WI-IATW.2006.6
 R. Agrawal, T. Imielinski and A. Swami, “Mining Association Rules between Sets of Items in Large Databases,” Proceedings of ACM International Conference on Management of Data (SIGMOD 93), Washington DC, 1993, pp. 207-216.
 J. Hipp, U. Guntzer and G. Nakhaeizadeh, “Algorithms for Association Rule Mining—A General Survey and Comparison,” ACM SIGKDD Explorations Newsletter, Vol. 2 No. 1, 2000, pp. 58-64. doi:10.1145/360402.360421
 P. H. Sharrod, “TreeBoost: Stochastic Gradient Boosting,” 2003. http://www.dtreg.com/treeboost.htm
 S. Axelsson, “Combining a Bayesian Classifier with Visualization: Understanding the IDS,” Proceedings of ACM Workshop on Visualization and Data Mining for Computer Security, New York, 2004, pp. 99-108.
 A. H. R. Karim, R. M. Rajatheva and K. M. Ahmed, “An Efficient Collaborative Intrusion Detection System for MANET Using Bayesian Approach,” Proceedings of 9th ACM International Symposium on Modeling Analysis and Simulation of Wireless and Mobile Systems (MSWiM ‘06), New York, 2006, pp. 187-190.
 P. Mell, V. Hu, R. Lippman, J. Haines and M. Zissman, “An Overview of Issues in Testing Intrusion Detection Systems” 2003. http://csrc.nist.gov/publications/PubsNISTIRs.html
 P. Fournier-Viger, “Computer Software Documentation,” 2008. http://www.philippe-fournierviger.com/spmf/