Exploring Forensic Data with Self-Organizing Maps
Baowei Fei, Jan H. P. Eloff, Hein S. Venter, Martin S. Olivier · Kluwer Academic Publishers eBooks · 2006
This paper discusses the application of a self-organizing map (SOM), an unsupervised learning neural network model, to support decision making by computer forensic investigators and assist them in conducting data analysis in a more efficient manner. A SOM is used to search for patterns in data sets and produce visual displays of the similarities in the data. The paper explores how a SOM can be used as a basis for further analysis. Also, it demonstrates how SOM visualization can provide investigators with greater abilities to interpret and explore data generated by computer forensic tools.