3LSPG: forensic tool evaluation by three layer stochastic process-based generation of data

Authors:
York Yannikos;Frederik Franke;Christian Winter;Markus Schneider
Affiliations:
Fraunhofer Institute for Secure Information Technology, Darmstadt, Germany;Fraunhofer Institute for Secure Information Technology, Darmstadt, Germany;Fraunhofer Institute for Secure Information Technology, Darmstadt, Germany;Fraunhofer Institute for Secure Information Technology, Darmstadt, Germany
Venue:
IWCF'10 Proceedings of the 4th international conference on Computational forensics
Year:
2010

Citing 6
Cited 0

Models and tools for quantitative assessment of operational security

Information systems security
A Synthetic Fraud Data Generation Methodology

ICICS '02 Proceedings of the 4th International Conference on Information and Communications Security
Synthesizing Test Data for Fraud Detection Systems

ACSAC '03 Proceedings of the 19th Annual Computer Security Applications Conference
Generation of synthetic data sets for evaluating the accuracy of knowledge discovery systems

Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Next-generation digital forensics

Communications of the ACM - Next-generation cyber forensics
Development of a Synthetic Data Set Generator for Building and Testing Information Discovery Systems

ITNG '06 Proceedings of the Third International Conference on Information Technology: New Generations

Quantified Score

Hi-index	0.00

Visualization

Abstract

Since organizations cannot prevent all criminal activities of employees by security technology in practice, the application of IT forensic methods for finding traces in data is extremely important. However, new attack variants for occupational crime require new forensic tools and specific environments may require adoptions of methods and tools. Obviously, the development of tools or their adaption require testing using data containing corresponding traces of attacks. Since real-world data are often not available synthetic data are necessary to perform testing. With 3LSPG we propose a systematic method to generate synthetic test data which contain traces of selected attacks. These data can then be used to evaluate the performance of different forensic tools.