Browsing NTNU Open by Author "Karresand, Nils Martin Mikael"

Now showing items 1-5 of 5

    • Creating a map of user data in NTFS to improve file carving 

      Karresand, Nils Martin Mikael; Warnqvist, Asalena; Lindahl, David; Axelsson, Stefan; Dyrkolbotn, Geir Olav (Journal article; Peer reviewed, 2019)
      Digital forensics and, especially, file carving are burdened by the large amounts of data that need to be processed. Attempts to solve this problem include efficient carving algorithms, parallel processing in the cloud and ...

    • Digital Forensic Usage of the Inherent Structures in NTFS 

      Karresand, Nils Martin Mikael (Doctoral theses at NTNU;2023:171, Doctoral thesis, 2023)
      Digital forensic investigators have for a long time been burdened by an increasing amount of data to handle. Many solutions have been proposed. A yet unexplored feature is to use the inherent structures left by the allocation ...

    • Disk Cluster Allocation Behavior in Windows and NTFS 

      Karresand, Nils Martin Mikael; Axelsson, Stefan; Dyrkolbotn, Geir Olav (Journal article; Peer reviewed, 2019)
      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 ...

    • An Empirical Study of the NTFS Cluster Allocation Behavior Over Time 

      Karresand, Nils Martin Mikael; Dyrkolbotn, Geir Olav; Axelsson, Stefan (Peer reviewed; Journal article, 2020)
      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 subfield of ...

    • Using NTFS cluster allocation behavior to find the location of user data 

      Karresand, Nils Martin Mikael; Axelsson, Stefan; Dyrkolbotn, Geir Olav (Journal article; Peer reviewed, 2019)
      Digital forensics is heavily affected by the large and increasing amount of data to be processed. To solve the problem there is ongoing research to find more efficient carving algorithms, use parallel processing in the ...