We live in a connected world where mobile devices are used by humans as valuable tools. The use of mobile devices leaves traces that can be treasured assets for a forensic analyst. Our aim is to investigate methods and exercise techniques that will merge all these valuable information in a way that will be efficient for a forensic analyst, producing graphical representations of the underlying data structures. We are using a framework able to collect and merge data from various sources and employ algorithms from a wide range of interdisciplinary areas to automate post-incident forensic analysis on mobile devices. © 2014 Springer International Publishing.
CITATION STYLE
Andriotis, P., Tryfonas, T., Oikonomou, G., Li, S., Tzermias, Z., Xynos, K., … Prevelakis, V. (2014). On the development of automated forensic analysis methods for mobile devices. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8564 LNCS, pp. 212–213). Springer Verlag. https://doi.org/10.1007/978-3-319-08593-7_17
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