Results 11 to 20 of about 142,585 (248)

Using NLP techniques for file fragment classification

Digital Investigation, 2012
Abstract The classification of file fragments is an important problem in digital forensics. The literature does not include comprehensive work on applying machine learning techniques to this problem. In this work, we explore the use of techniques from natural language processing to classify file fragments.
Simran Fitzgerald, George Mathews, Colin W. Morris, Oles Zhulyn   +3 more
exaly   +4 more sources

ByteNet: Rethinking Multimedia File Fragment Classification through Visual Perspectives [PDF]

IEEE Transactions on Multimedia
Accepted in ...
Wenyang Liu, Kejun Wu, Tianyi Liu, Yi Wang, Kim–Hui Yap, Lap‐Pui Chau   +5 more
exaly   +5 more sources

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, Tu-Thach Quach, Jason Wheeler, James B. Aimone, Conrad D. James   +4 more
exaly   +5 more sources

Intra- and inter-sector contextual information fusion with joint self-attention for file fragment classification

Knowledge-Based Systems
File fragment classification (FFC) aims to identify the file type of file fragments in memory sectors, which is of great importance in memory forensics and information security. Existing works focused on processing the bytes within sectors separately and ignoring contextual information between adjacent sectors.
Yi Wang, Wenyang Liu, Kejun Wu, Kim–Hui Yap, Lap‐Pui Chau   +4 more
exaly   +5 more sources

Fragments-Expert: A Graphical User Interface MATLAB Toolbox for\n Classification of File Fragments [PDF]

Concurrency and Computation: Practice and Experience, 2020
SummaryThe classification of file fragments of various file formats is an essential task in various applications such as firewalls, intrusion detection systems, antiviruses, web content filtering, and digital forensics. However, the community lacks a suitable software tool that can integrate major methods for feature extraction from file fragments and ...
Mehdi Teimouri, Zahra Seyedghorban, Fatemeh Amirjani   +2 more
  +7 more sources

File Fragment Classification-The Case for Specialized Approaches [PDF]

2009 Fourth International IEEE Workshop on Systematic Approaches to Digital Forensic Engineering, 2009
Increasingly advances in file carving, memory analysis and network forensics requires the ability to identify the underlying type of a file given only a file fragment. Work to date on this problem has relied on identification of specific byte sequences in file headers and footers, and the use of statistical analysis and machine learning algorithms ...
Vassil Roussev, Simson Garfinkel
openalex   +4 more sources

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, Candice Quates
openalex   +2 more sources

A Byte Sequence is Worth an Image: CNN for File Fragment Classification Using Bit Shift and n-Gram Embeddings [PDF]

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.
Wenyang Liu, Yi Wang, Kejun Wu, Kim–Hui Yap, Lap‐Pui Chau   +4 more
  +6 more sources

ByteRCNN: Enhancing File Fragment Type Identification With Recurrent and Convolutional Neural Networks

IEEE Access, 2023
File fragment type identification is an important step in file carving and data recovery. Machine learning techniques, especially neural networks, have been utilized for this problem, some with very promising results.
Kristian Skracic, Juraj Petrovic, Predrag Pale   +2 more
doaj   +3 more sources

Approaches to the classification of high entropy file fragments [PDF]

Digital Investigation, 2013
In this paper we propose novel approaches to the problem of classifying high entropy file fragments. We achieve 97% correct classification for encrypted fragments and 78% for compressed. Although classification of file fragments is central to the science of Digital Forensics, high entropy types have been regarded as a problem. Roussev and Garfinkel [1]
Philip Penrose, Richard Macfarlane, William J. Buchanan   +2 more
openalex   +3 more sources