Paper Info
Title
Synthetic Data Creation for Forensic Tool Testing: Improving Performance of the 3LSPG Framework
Abstract
Increasing amounts of data require improvements in effectiveness and efficiency of forensic tools. If new tools have been developed, they have to be evaluated, e.g. by applying test data. 3LSPG has recently been proposed as a framework for generating synthetic test data by simulating activities of subjects using Markov chains. However, the generation of test data should also be efficient. In this paper, we show how to improve the efficiency of 3LSPG considerably compared to its original proposal. We show how to speed-up the calculation of state transition probabilities in the Markov model of 3LSPG by proposing an algorithm that is much faster and more reliable than the one originally used. The simplex algorithm serves as basis for our algorithm although it is typically used for the different purpose of solving optimization problems. Our algorithm helps to enable the creation of synthetic data for forensic tool testing with 3LSPG in significantly shorter time.
Year
DOI
Venue
2012
10.1109/ARES.2012.46
ARES
Keywords
Field
DocType
3lspg framework,model-based simulation,different purpose,markov chains,state transition probabilities,improving performance,synthetic test data,forensic tool testing,three layer stochastic process-based generation of data,testing,computer forensics,markov model,linear programming,simplex algorithm,synthetic data creation,synthetic test data genertaion,synthetic data,forensic tool,new tool,test data,markov processes,markov chain,probability,synthetic data generation
Data mining,Simplex algorithm,Markov process,Computer science,Markov model,Markov chain,Markov decision process,Synthetic data,Artificial intelligence,Linear programming,Test data,Machine learning
Conference
ISBN
Citations 
PageRank 
978-1-4673-2244-7
4
0.62
References 
Authors
6
3
Name
Order
Citations
PageRank
York Yannikos1437.60
Christian Winter2243.19
Markus Schneider3626.33