Author URLs
Professor Breitinger's Faculty Profile
Professor Breitinger's web page
Document Type
Article
Publication Date
3-2019
Subject: LCSH
Computer crimes--Investigation, Cyber forensics
Disciplines
Computer Engineering | Computer Sciences | Electrical and Computer Engineering
Abstract
Crimes involving digital evidence are getting more complex due to the increasing storage capacities and utilization of devices. Event reconstruction (i.e., understanding the timeline) is an essential step for investigators to understand a case where a prominent tool is Log2Timeline (a tool that creates super timelines which is a combination of several log files and events throughout a system). While these timelines provide great evidence and help to understand a case, they are complex and require tools as well as training scenarios. In this paper we present Timeline2GUI an easy-to-use python implementation to analyze CSV log files create by Log2Timeline. Additionally, we present three training scenarios – beginner, intermediate and advanced – to practice timeline analysis skills as well as familiarity with visualization tools. Lastly, we provide a comprehensive overview of tools.
DOI
10.1016/j.diin.2018.12.004
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Repository Citation
Debinski, Mark; Mohan, Parvathy; and Breitinger, Frank, "Timeline2GUI: A Log2Timeline CSV Parser and Training Scenarios" (2019). Electrical & Computer Engineering and Computer Science Faculty Publications. 84.
https://digitalcommons.newhaven.edu/electricalcomputerengineering-facpubs/84
Publisher Citation
Debinski, Mark, Frank Breitinger, and Parvathy Mohan. "Timeline2GUI: A Log2Timeline CSV parser and training scenarios." Digital Investigation (2018). Volume 28, March 2019, Pages 34-43.
Included in
Computer Engineering Commons, Computer Sciences Commons, Electrical and Computer Engineering Commons
Comments
This is the authors' accepted version of the article published in Digital Investigation. The version of record can be found at http://dx.doi.org/10.1016/j.diin.2018.12.004