| 1. |
- Karresand, Martin, et al.
(författare)
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An Empirical Study of the NTFS Cluster Allocation Behavior Over Time
- 2020
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Ingår i: Forensic Science International: Digital Investigation. - : Elsevier Ltd. - 2666-2817 .- 2666-2825. ; 33
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Tidskriftsartikel (refereegranskat)abstract
- © 2020 The Author(s)The amount of data to be handled in digital forensic investigations is continuously increasing, while the tools and processes used are not developed accordingly. This especially affects the digital forensic sub-field of file carving. The use of the structuring of stored data induced by the allocation algorithm to increase the efficiency of the forensic process has been independently suggested by Casey and us. Building on that idea we have set up an experiment to study the allocation algorithm of NTFS and its behavior over time from different points of view. This includes if the allocation algorithm behaves the same regardless of Windows version or size of the hard drive, its adherence to the best fit allocation strategy and the distribution of the allocation activity over the available (logical) storage space. Our results show that space is not a factor, but there are differences in the allocation behavior between Windows 7 and Windows 10. The results also show that the allocation strategy favors filling in holes in the already written area instead of claiming the unused space at the end of a partition and that the area with the highest allocation activity is slowly progressing from approximately 10 GiB into a partition towards the end as the disk is filling up.
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| 2. |
- Karresand, M., et al.
(författare)
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Disk Cluster Allocation Behavior in Windows and NTFS
- 2020
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Ingår i: Mobile Networks and Applications. - : Springer. - 1383-469X .- 1572-8153. ; 5:1, s. 248-258
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Tidskriftsartikel (refereegranskat)abstract
- The allocation algorithm of a file system has a huge impact on almost all aspects of digital forensics, because it determines where data is placed on storage media. Yet there is only basic information available on the allocation algorithm of the currently most widely spread file system; NTFS. We have therefore studied the NTFS allocation algorithm and its behavior empirically. To do that we used two virtual machines running Windows 7 and 10 on NTFS formatted fixed size virtual hard disks, the first being 64 GiB and the latter 1 TiB in size. Files of different sizes were written to disk using two writing strategies and the $Bitmap files were manipulated to emulate file system fragmentation. Our results show that files written as one large block are allocated areas of decreasing size when the files are fragmented. The decrease in size is seen not only within files, but also between them. Hence a file having smaller fragments than another file is written after the file having larger fragments. We also found that a file written as a stream gets the opposite allocation behavior, i. e. its fragments are increasing in size as the file is written. The first allocated unit of a stream written file is always very small and hence easy to identify. The results of the experiment are of importance to the digital forensics field and will help improve the efficiency of for example file carving and timestamp verification. © 2019, The Author(s).
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| 3. |
- Nordvik, Rune, et al.
(författare)
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Generic Metadata Time Carving
- 2020
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Ingår i: Forensic Science International: Digital Investigation. - Oxford : Elsevier. - 2666-2817 .- 2666-2825. ; 33:S
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Tidskriftsartikel (refereegranskat)abstract
- Recovery of files can be a challenging task in file system investigations, and most carving techniques are based on file signatures or semantics within the file. However, these carving techniques often only recover the files, but not the metadata associated with the file. In this paper, we propose a novel, generic approach for carving metadata by searching for equal and co-located timestamps. The rationale is that there are some common metadata for files and directories within each file system. Our generic time carver provides potential timestamp locations for repeated timestamps in each metadata structure, identifying potential metadata for files. A semantic parser then filters the results with respect to the specific file system type. In our experiments, extraction of MFT entries in NTFS and inodes in Ext4 had near perfect precision for metadata entries with multiple equivalent timestamps, and for such metadata structures we obtained perfect recall for NTFS. For known file systems, we use the information found within identified metadata to recover files, and by recovering files and their associated metadata we increase the evidential value of recovered files. © 2020 The Author(s)
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