Identifying forensically uninteresting files in a large corpus
For digital forensics, eliminating the uninteresting is often more critical than finding the interesting. We discuss methods exploiting the metadata of a large corpus. Tests were done with an international corpus of 262.7 million files obtained from 4018 drives. For malware investigations, we show t...
Main Author: | N. C. Rowe |
---|---|
Format: | Article |
Language: | English |
Published: |
European Alliance for Innovation (EAI)
2016-12-01
|
Series: | EAI Endorsed Transactions on Security and Safety |
Subjects: | |
Online Access: | http://eudl.eu/doi/10.4108/eai.8-12-2016.151725 |
Similar Items
-
Application Whitelisting : Smartphones in High Security Environments
by: Bildsten, Caroline
Published: (2013) -
A Heuristic Featured Based Quantification Framework for Efficient Malware Detection. Measuring the Malicious intent of a file using anomaly probabilistic scoring and evidence combinational theory with fuzzy hashing for malware detection in Portable Executable files
by: Namanya, Anitta P.
Published: (2018) -
Do Metadata-based Deleted-File-Recovery (DFR) Tools Meet NIST Guidelines?
by: Andrew Meyer, et al.
Published: (2019-08-01) -
Respon Masyarakat terhadap Sistem Whitelist: Alternatif untuk Akses Internet yang Lebih Aman
by: Emyana Ruth Eritha Sirait
Published: (2017-01-01) -
Computer Forensics Method in Analysis of Files Timestamps in Microsoft Windows Operating System and NTFS File System
by: Vesta Sergeevna Matveeva, et al.
Published: (2013-02-01)