Future Challenges for Digital Forensics (8)

Question 1

What is considered the main future challenge for digital forensics?

Answer 1

The huge amount unstructured data investigators must look through is already the main hurdle for investigators. This issue is likely to grow in severity as more and more devices and applications become interconnected. The amount of unstructured data is a challenge for all phases in digital forensics investigations

Question 2

How may the different phases be aided by enhanced automation?

Answer 2

Identification - Can be aided by intelligent detection and identification methods.

Collection - Can be made more efficient by upgraded remote acquisition tools with in-built integrity assurance.

Examination - Can be simplified through automated data recovery, e.g., deleted files, and data reduction (ignore unimportant files).

Analysis - Can be leverage computational methods such as ML algorithms to identify patterns and data that may be of interest as evidence.

Presentation - Can benefit from a wide range of visualization tools as well as in-built report generation.

Question 3

What is Computational Forensics?

Answer 3

Computational Forensics is the usage of computational methods in forensics investigations. In a nutshell, computational methods utilize techniques from computer science and applied mathematics to perform classification or clustering of data. Computational techniques are increasingly being adopted by investigators as there is a strong need for a more capable toolkit. The main advantage with computational forensics is the opportunity to automate many labour intensive tasks that previously required several valuable hours of labour. Freeing up investigators from such tasks allow them to focus more of their efforts on the most important tasks in the investigation