On the development of automated forensic analysis methods for mobile devices

Andriotis, Panagiotis; Tryfonas, Theo; Oikonomou, George; Li, Shancang; Tzermias, Zacharias; Xynos, Konstantinos; Read, Huw; Prevelakis, Vassilis

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.

Citation

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. Lecture Notes in Artificial Intelligence, 8564 LNCS, 212-213. https://doi.org/10.1007/978-3-319-08593-7_17

• Journal Article Type: Article
• Acceptance Date: Jun 30, 2014
• Publication Date: Jan 1, 2014
• Journal: Lecture Notes in Computer Science
• Print ISSN: 0302-9743
• Publisher: Springer Verlag
• Peer Reviewed: Peer Reviewed
• Volume: 8564
• Pages: 212-213
• Book Title: Trust and Trustworthy Computing
• DOI: https://doi.org/10.1007/978-3-319-08593-7_17
• Keywords: steganalysis, smartphone, sentiment analysis, post-incident, SMS, social media, forensics, Android
• Public URL: https://uwe-repository.worktribe.com/output/822847
• Publisher URL: http://dx.doi.org/10.1007/978-3-319-08593-7_17
• Additional Information: Title of Conference or Conference Proceedings : 7th International Conference, TRUST 2014