CEC Theses and Dissertations

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Date of Award

2011

Document Type

Dissertation - NSU Access Only

Degree Name

Doctor of Philosophy in Computer Information Systems (DCIS)

Department

Graduate School of Computer and Information Sciences

Advisor

James D Cannady

Committee Member

Junping Sun

Committee Member

Daniel P Shoemaker

Abstract

Intrusion detection is difficult to accomplish when attempting to employ current methodologies when considering the database and the authorized entity. It is a common understanding that current methodologies focus on the network architecture rather than the database, which is not an adequate solution when considering the insider threat. Recent findings suggest that many have attempted to address this concern with the utilization of various detection methodologies in the areas of database authorization, security policy management and behavior analysis but have not been able to find an adequate solution to achieve the level of detection that is required.

While each of these methodologies has been addressed on an individual basis, there has been very limited work to address the methodologies as a single entity in an attempt to function within the detection environment in a harmonious fashion. Authorization is at the heart of most database implementations however, is not enough to prevent a rogue, authorized entity from instantiating a malicious action. Similarly, eliminating the current security policies only exacerbates the problem due to a lack of knowledge in a fashion when the policies have been modified. The behavior of the authorized entity is the most significant concern in terms of intrusion detection. However, behavior identification methodologies alone will not produce a complete solution. The detection of the insider threat during database access by merging the individual intrusion detection methodologies as noted will be investigated.

To achieve the goal, this research is proposing the creation of a procedural framework to be implemented as a precursor to the effecting of the data retrieval statement. The intrusion model and probability thresholds will be built utilizing the intrusion detection standards as put forth in research and industry. Once an intrusion has been indicated, the appropriate notifications will be distributed for further action by the security administrator while the transaction will continue to completion.

This research is proposing the development of a Database Intrusion Detection framework with the introduction of a process as defined in this research, to be implemented prior to data retrieval. This addition will enable an effective and robust methodology to determine the probability of an intrusion by the authorized entity, which will ultimately address the insider threat phenomena.

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