Abstract
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.
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References
Andriotis, P., Oikonomou, G., Tryfonas, T.: Forensic Analysis of Wireless Networking Evidence of Android Smartphones. In: WIFS, pp. 109–114 (2012)
Andriotis, P., Oikonomou, G., Tryfonas, T.: JPEG Steganography Detection with Benford’s Law. Digital Investigation 9(3), 246–257 (2013)
Andriotis, P., Tzermias, Z., Mparmpaki, A., Ioannidis, S., Oikonomou, G.: Multilevel Visualization Using Enhanced Social Network Analysis with Smartphone Data. IJDCF 5(4), 34–54 (2013)
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Andriotis, P. et al. (2014). On the Development of Automated Forensic Analysis Methods for Mobile Devices. In: Holz, T., Ioannidis, S. (eds) Trust and Trustworthy Computing. Trust 2014. Lecture Notes in Computer Science, vol 8564. Springer, Cham. https://doi.org/10.1007/978-3-319-08593-7_17
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DOI: https://doi.org/10.1007/978-3-319-08593-7_17
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-08592-0
Online ISBN: 978-3-319-08593-7
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