Synthesizing test data for fraud detection systems

被引：42

作者：

Barse, EL ^{[1
]}

Kvarnström, H ^{[1
]}

Jonsson, E ^{[1
]}

机构：

[1] Chalmers Univ Technol, Dept Comp Engn, S-41296 Gothenburg, Sweden

来源：

19TH ANNUAL COMPUTER SECURITY APPLICATIONS CONFERENCE, PROCEEDINGS | 2003年

关键词：

D O I：

10.1109/CSAC.2003.1254343

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper reports an experiment aimed at generating synthetic test data for fraud detection in an IP based video-on-demand service. The data generation verifies a methodology previously developed by the present authors [7] that ensures that important statistical properties of the authentic data are preserved by using authentic normal data and fraud as a seed for generating synthetic data. This enables us to create realistic behavior profiles for users and attackers. The data can also be used to train the fraud detection system itself thus creating the necessary adaptation of the system to a specific environment. Here we aim to verify the usability and applicability of the synthetic data, by using them to train a fraud detection system. The system is then exposed to a set of authentic data to measure parameters such as detection capability and false alarm rate as well as to a corresponding set of synthetic data, and the results are compared.

引用

页码：384 / 394

页数：11