Automatic Evaluation of Information Ordering: Kendall's Tau
Computational Linguistics
Detecting anomalous access patterns in relational databases
The VLDB Journal — The International Journal on Very Large Data Bases
Knowledge Acquisition and Insider Threat Prediction in Relational Database Systems
CSE '09 Proceedings of the 2009 International Conference on Computational Science and Engineering - Volume 03
M-score: estimating the potential damage of data leakage incident by assigning misuseability weight
Proceedings of the 2010 ACM workshop on Insider threats
A data-centric approach to insider attack detection in database systems
RAID'10 Proceedings of the 13th international conference on Recent advances in intrusion detection
Hi-index | 0.00 |
In previous work we proposed the M-score measure for assigning a misuseability (i.e., sensitivity) score to data records. The M-score uses sensitivity score functions that should be acquired from domain experts. In this paper we present two different approaches for acquiring the required knowledge. In the first method the expert is asked to explicitly assign a sensitivity score to displayed records. The second method employs pairwise comparison approach. A field study indicates that the later method is preferable.