Machine learning in digital forensics: a systematic literature review
T Nayerifard, H Amintoosi, AG Bafghi… - arXiv preprint arXiv …, 2023 - arxiv.org
Development and exploitation of technology have led to the further expansion and
complexity of digital crimes. On the other hand, the growing volume of data and …
complexity of digital crimes. On the other hand, the growing volume of data and …
ByteRCNN: Enhancing File Fragment Type Identification with Recurrent and Convolutional Neural Networks
K Skračić, J Petrović, P Pale - IEEE access, 2023 - ieeexplore.ieee.org
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 …
Machine learning techniques, especially neural networks, have been utilized for this …
Classification of Low-and High-Entropy File Fragments Using Randomness Measures and Discrete Fourier Transform Coefficients
K Skračić, J Petrović, P Pale - Vietnam journal of computer science, 2023 - World Scientific
This paper presents an approach to improve the file fragment classification by proposing
new features for classification and evaluating them on a dataset that includes both low-and …
new features for classification and evaluating them on a dataset that includes both low-and …
File fragment classification using light-weight convolutional neural networks
In digital forensics, file fragment classification is an important step toward completing file
carving process. There exist several techniques to identify the type of file fragments without …
carving process. There exist several techniques to identify the type of file fragments without …
A Byte Sequence is Worth an Image: CNN for File Fragment Classification Using Bit Shift and n-Gram Embeddings
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 …
forensics and Internet security. Existing methods mainly treat file fragments as 1d byte …
LSDStrategy: A lightweight software-driven strategy for addressing big data variety of multimedia streaming
SD Khudhur, HA Jeiad - IEEE Access, 2022 - ieeexplore.ieee.org
Many devices, users, and applications stream an irregular amount of varied data every
second. This rapid generation of data continues at an enormous rate, constructing the big …
second. This rapid generation of data continues at an enormous rate, constructing the big …
Intra-and inter-sector contextual information fusion with joint self-attention for file fragment classification
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 …
sectors, which is of great importance in memory forensics and information security. Existing …
Sift–file fragment classification without metadata
S Alam - 2023 3rd International Conference on Computing and …, 2023 - ieeexplore.ieee.org
A vital issue of file carving in digital forensics is type classification of file fragments when the
filesystem metadata is missing. Over the past decades, there have been several efforts for …
filesystem metadata is missing. Over the past decades, there have been several efforts for …
File Fragment Type Identification Based on CNN and LSTM
N Zhu, Y Liu, K Wang, C Ma - Proceedings of the 2023 7th International …, 2023 - dl.acm.org
In digital forensics, file carving is the process of recovering files on a storage media without
any file system information. Note that when a file is deleted, the file system does not zero-out …
any file system information. Note that when a file is deleted, the file system does not zero-out …
XMP: A Cross-Attention Multi-Scale Performer for File Fragment Classification
File fragment classification (FFC) is the task of identifying the file type given a small fraction
of binary data, and serves a crucial role in digital forensics and cybersecurity. Recent studies …
of binary data, and serves a crucial role in digital forensics and cybersecurity. Recent studies …