Minitrack 1: Digital Forensics, Data Analytics and Data Security
Description
Cloud computing, on-demand services, mobile devices and the Internet of Things have spawned a tremendous growth in data available to forensic analysts. This deluge has created several challenges, including how to effectively search data for valuable information, effectively exploit different sources of information, and detect and handle incomplete or falsified data (coined as big forensic data challenges by Quick and Choo). Furthermore, the ephemeral nature of (cloud) containers and virtual machines, along with improved security, have created challenges in the collection and preservation of data. Auspiciously, the data analytic fields, such as visual analytics, machine learning, big data, and ontological reasoning, have made great progress with respect to searching large amounts of disparate data, removing and correcting erroneous information, and generating actionable knowledge. This mini-track seeks innovative work that leverages data analytic methods to improve data security, enhance digital forensics investigations and/or aid in resolving current digital forensic challenges.Please go to here for more informaton about this and other minitracks and to this link for submission information.
Important Dates
- Submit Papers: February 28, 2018
- Decisions made: April 18, 2018
- Camera Ready Version: April 25, 2018
Track Chairs
- Ryan Benton: rbenton@southalabama.edu
- William Glisson: bglisson@southalabama.edu
- Kim-Kwang Raymond Choo: raymond.choo@utsa.edu
- Raju Gottumukkala: nrg0821@louisiana.edu