EconPapers    
Economics at your fingertips  
 

X_myKarve: Non-Contiguous JPEG File Carver

Nurul Azma Abdullah
Additional contact information
Nurul Azma Abdullah: Universiti Tun Hussein Onn Malaysia, Batu Pahat, Malaysia

International Journal of Digital Crime and Forensics (IJDCF), 2016, vol. 8, issue 3, 63-84

Abstract: Many studies have been conducted in addressing problem of fragmented JPEG. However, carving fragmented JPEG files are not easy to solve due to the complexity of determining the fragmentation point. In this article, X_myKarvee framework is introduced to address the fragmentation issues that occur in JPEG images. X_myKarve introduce a new technique, deletion by binary search to detect fragmentation point which is used to separate a file into several individual fragments. These fragments are then reassembled with the correct pairs which form a complete and correct image. X_myKarve is tested using various datasets namely DFRWS 2006 and DFRWS 2007. The result shows that X_myKarve is capable of carving over 20% more than myKarve and RevIt for DFRWS 2006 datasets where X_myKarve can carve intertwined fragmented JPEG images completely compared to myKarve and RevIt. X_myKarve is a good alternative for carving fragmented JPEG files intertwined with each other.

Date: 2016
References: Add references at CitEc
Citations: Track citations by RSS feed

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 018/IJDCF.2016070105 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jdcf00:v:8:y:2016:i:3:p:63-84

Access Statistics for this article

More articles in International Journal of Digital Crime and Forensics (IJDCF) from IGI Global
Bibliographic data for series maintained by Journal Editor ().

 
Page updated 2019-11-24
Handle: RePEc:igg:jdcf00:v:8:y:2016:i:3:p:63-84