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

Yannikos, York ; Franke, Frederik ; Winter, Christian ; Schneider, Markus
eds.: Sako, Hiroshi ; Franke, Katrin ; Saitoh, Shuji (2011)
3LSPG: Forensic Tool Evaluation by Three Layer Stochastic Process-Based Generation of Data.
Tokyo, Japan
doi: 10.1007/978-3-642-19376-7_18
Conference or Workshop Item, Bibliographie

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 ; Franke, Katrin ; Saitoh, Shuji
Creators: Yannikos, York ; Franke, Frederik ; Winter, Christian ; Schneider, Markus
Type of entry: Bibliographie
Title: 3LSPG: Forensic Tool Evaluation by Three Layer Stochastic Process-Based Generation of Data
Language: English
Date: February 2011
Publisher: Springer
Book Title: Computational Forensics, Fourth International Workshop, IWCF 2010, Tokyo, Japan, November 11–12, 2010, Revised Selected Papers
Series: LNCS
Series Volume: 6540
Event Location: Tokyo, Japan
DOI: 10.1007/978-3-642-19376-7_18
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.

Uncontrolled Keywords: Secure Data;White collar crime, synthetic data, Markov chains
Identification Number: TUD-CS-2010-0202
Divisions: LOEWE > LOEWE-Zentren > CASED – Center for Advanced Security Research Darmstadt
LOEWE > LOEWE-Zentren
LOEWE
Date Deposited: 30 Dec 2016 20:23
Last Modified: 17 May 2018 13:02
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