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File fragment encoding classification—An empirical approach
Digital Investigation, 2013 Over the past decade, a substantial effort has been put into developing methods to classify file fragments. Throughout, it has been an article of faith that data fragments, such as disk blocks, can be attributed to different file types. This work is an attempt to critically examine the underlying assumptions and compare them to empirically collected ...
Vassil Roussev
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GenSpec: A File Fragment Classification Approach
2020 International Conference on Computing and Information Technology (ICCIT-1441), 2020Collection and analysis of data are at the heart of digital forensics. However, in real-life situations, the data of interest is often found in files that were partially erased or otherwise tampered with. Consequently, identification of the file types of those fragmented files and the data format of the text contained in each file are deemed necessary.
Firas Layth Khaleel
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File Fragment Classification with Focus on OLE and OOXML classes
2020 43rd International Convention on Information, Communication and Electronic Technology (MIPRO), 2020Classification of file fragments is a crucial step in digital forensics and determining file types based on available data fragments. Currently explored file fragment classification methods other than forensic hand-examination rely on machine learning techniques. Those methods most commonly use features based on byte frequency distribution as inputs in
J Petrović, Predrag Pale
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Anomaly Detection in File Fragment Classification of Image File Formats
2021 11th International Conference on Computer Engineering and Knowledge (ICCKE), 2021Mehdi Teimouri
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File Fragment Type Classification by Bag-Of-Visual-Words.
ISC Int. J. Inf. Secur., 2021File fragment’s type classification in the absence of header and file system information, is a major building block in various solutions devoted to file carving, memory analysis and network forensics. Over the past decades, a substantial amount of effort has been put into developing methods to classify file fragments.
Erfan, Mina, Jalili, Saeed
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Sparse Coding for N-Gram Feature Extraction and Training for File Fragment Classification
IEEE Transactions on Information Forensics and Security, 2018 File fragment classification is an important step in the task of file carving in digital forensics. In file carving, files must be reconstructed based on their content as a result of their fragmented storage on disk or in memory. Existing methods for classification of file fragments typically use hand-engineered features, such as byte histograms or ...
Felix Wang +2 more
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Neural Networks for File Fragment Classification
2019 42nd International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), 2019Abstract - File fragment classification is an important step in file forensics in which filetypes are assumed based on their available content fragments. Methods typically used for this task utilize machine learning techniques on features like byte frequency distributions and fragment entropy measures.
J Petrović +2 more
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ByteNet: Rethinking Multimedia File Fragment Classification Through Visual Perspectives
IEEE Transactions on MultimediaAccepted in ...
Kim-Hui Yap +2 more
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Classification and Recovery of Fragmented Multimedia Files using the File Carving Approach
International Journal of Mobile Computing and Multimedia Communications, 2013File carving is a recovery technique which does not consider file tables or other meta-data which is used to organize data on storage media. As files can be recovered based only on their content and/or structure, this technique is an indispensable task during digital investigations.
Rainer Poisel +3 more
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2023 IEEE 5th International Conference on Artificial Intelligence Circuits and Systems (AICAS), 2023 File fragment classification (FFC) on small chunks of memory is essential in memory forensics and Internet security. Existing methods mainly treat file fragments as 1d byte signals and utilize the captured inter-byte features for classification, while the bit information within bytes, i.e., intra-byte information, is seldom considered.
Kim-Hui Yap, Lap-Pui Chau
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