Title
Detecting Malicious Insider Threats using a Null Affinity Temporal Three Dimensional Matrix Relation
Abstract
A new approach for detecting malicious access to a database system is proposed and tested in this work. The proposed method relies upon manipulating usage information from database logs into three dimensional null-related matrix clusters that reveals new information about which sets of data items should never be related during defined temporal time frames across several applications. If access is detected in these three dimensional null-related clusters, this is an indication of illicit behavior, and further security procedures should occur. In this paper, we describe the null affinity algorithm and illustrate by several examples its use for problem decomposition and access control to data items which should not be accessed together, resulting in a new and novel way to detect malicious access that has never been proposed before.
Year
Venue
Keywords
2009
SECURITY IN INFORMATION SYSTEMS, PROCEEDINGS
three dimensional
DocType
Citations 
PageRank 
Conference
1
0.37
References 
Authors
0
5
Name
Order
Citations
PageRank
Jonathan White110.37
Brajendra Panda233139.58
Quassai Yassen310.37
Khanh Nguyen412810.39
Weihan Li531.10