![]() ![]() This study will serve as a reference for scientists to evaluate different strategies and obstacles for carving so that they may choose the suitable carving approaches for their study and also future developments. We are also able to highlight several of the challenges for file carving mentioned in the past research. We classify the carving approach into five classifications which are general carving, carving by specific file type, carving by structure, carving by the file system, and carving by fragmentation. Based on the analysis, we are able to state the current state of the art of file carving. This analysis is done to consider several perspectives which are the current research direction of the file carving approach, the classification for the file carving approaches, and also the challenges are to be highlighted. A review is carried out reviewing different works of literature covering various aspects of carving approaches from multiple digital data sources including IEEE Xplore, Google Scholar, Web of Science, etc. With the increasing numbers of literature that are covering this research area, there is a need to review this literature for further reference. There is a lot of research being done in developing file carving approaches and different researches focused on different aspects. Data restoration and analysis on file systems is one of digital forensic science’s most fundamental practices. This paper will be a guide for researchers searching for carving techniques in order to choose the appropriate carving algorithm and to continue improving it in the future.ĭigital forensics is a crucial process of identifying, conserving, retrieving, evaluating, and documenting digital evidence obtained on computers and other electronic devices. This paper is divided into two sections, the first section is the traditional carving approach and the second section is the advanced carving approach. These techniques are also classified according to the carving method styles used and the fragmentation issues as well as the type of a file system since these techniques rely on the content and the file structure of the particular file to be carved. The key contribution of this paper is the study and analysis of current existing file carving techniques for file carving in order to define their functionality. This paper focuses mainly on the different types of carving techniques commonly used based on particular circumstances. There are various styles of file carving techniques used for types of files, including PDF, JPEG, XML and etc. In general, carving is used to retrieve data with the absence of metadata that point to the content. File carving is a technique used to retrieve data other than data recovery technique and data restoration technique. Although errors due to detection of image width, placement of image blocks, and color and brightness adjustments can occur, these errors reduce significantly when fragment sizes are larger than 32 KiB.įile carving is a method that enables researchers to collect data from unallocated memory space. Recovery results on a variety of JPEG file fragments show that given the knowledge of Huffman code tables, our technique can very reliably identify the remaining decoder settings for all fragments of size 4 KiB or above. Second, it determines the spatial domain parameters to produce a perceptually meaningful image. First, it decompresses the incomplete file data to obtain a spatial domain representation. Our carving approach utilizes this information in a new technique that performs two tasks. To realize this, we examined JPEG file headers of a large number of images collected from Flickr photo sharing site to identify their structural characteristics. In this work, we advance the state-of-theart in JPEG file carving by introducing the ability to recover fragments of a JPEG file when the associated file header is missing. When data are encoded and compressed, the current paradigm of carving requires the knowledge of the compression and encoding settings to succeed. File carving techniques allow for recovery of files from storage devices in the absence of any file system metadata. ![]()
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