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3LSPG: Forensic Tool Evaluation by Three Layer Stochastic Process-Based Generation of Data

Yannikos, York and Franke, Frederik and Winter, Christian and Schneider, Markus Sako, Hiroshi and Franke, Katrin and Saitoh, Shuji (eds.) (2011):
3LSPG: Forensic Tool Evaluation by Three Layer Stochastic Process-Based Generation of Data.
In: LNCS, 6540, In: Computational Forensics, Fourth International Workshop, IWCF 2010, Tokyo, Japan, November 11–12, 2010, Revised Selected Papers, pp. 200–211,
Springer, Tokyo, Japan, ISBN 978-3-642-19375-0,
DOI: 10.1007/978-3-642-19376-7_18,
[Conference or Workshop Item]

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.

Item Type: Conference or Workshop Item
Erschienen: 2011
Editors: Sako, Hiroshi and Franke, Katrin and Saitoh, Shuji
Creators: Yannikos, York and Franke, Frederik and Winter, Christian and Schneider, Markus
Title: 3LSPG: Forensic Tool Evaluation by Three Layer Stochastic Process-Based Generation of Data
Language: ["languages_typename_1" not defined]
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.

Title of Book: Computational Forensics, Fourth International Workshop, IWCF 2010, Tokyo, Japan, November 11–12, 2010, Revised Selected Papers
Series Name: LNCS
Volume: 6540
Publisher: Springer
ISBN: 978-3-642-19375-0
Uncontrolled Keywords: Secure Data;White collar crime, synthetic data, Markov chains
Divisions: LOEWE > LOEWE-Zentren > CASED – Center for Advanced Security Research Darmstadt
LOEWE > LOEWE-Zentren
LOEWE
Event Location: Tokyo, Japan
Date Deposited: 30 Dec 2016 20:23
DOI: 10.1007/978-3-642-19376-7_18
Identification Number: TUD-CS-2010-0202
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