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(to be completed)

 


ThinkMind // International Journal On Advances in Security, volume 9, numbers 1 and 2, 2016 // View article sec_v9_n12_2016_2


MoNA: Automated Identification of Evidence in Forensic Short Messages

Authors:
Michael Spranger
Florian Heinke
Luisa Appelt
Marcus Puder
Dirk Labudde

Keywords: forensic; ontology; German; text processing; expert system; text analysis; short messages

Abstract:
Mobile devices are a popular means for planning, appointing and conducting criminal offences. In particular, short messages (SMS) and chats often contain evidential information. Due to the terms of their use, these types of messages are fundamentally different from other forms of written communication in terms of their grammatical and syntactic structure. Due to the low price of media storage, messages are rarely deleted. On one hand, this fact is quite positive as potentially evidential information is not lost. On the other hand, considering only SMSs, 15,000 and more stored only on one mobile phone is not uncommon. In most cases of organized or gang crime, there is not one but many devices in use. Analysing this large amount of messages manually is time consuming and, therefore, not economically justifiable in the cases of small and medium crimes. In this work, we propose a process chain that enables to decrease the analysis and evaluation time dramatically by reducing the amount of messages, that need to be examined manually. We further present an implemented prototype (MoNA, mobile network analyzer) and demonstrate its performance.

Pages: 14 to 24

Copyright: Copyright (c) to authors, 2016. Used with permission.

Publication date: June 30, 2016

Published in: journal

ISSN: 1942-2636

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