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ByteNet: Rethinking Multimedia File Fragment Classification Through Visual Perspectives

IEEE Transactions on Multimedia
Multimedia file fragment classification (MFFC) aims to identify file fragment types, e.g., image/video, audio, and text without system metadata. It is of vital importance in multimedia storage and communication.
Yi Wang, wenyang Liu, Kim-Hui Yap
exaly   +1 more source

Interpretability and Transparency of Machine Learning in File Fragment Analysis with Explainable Artificial Intelligence

Electronics
Machine learning models are increasingly being used across diverse fields, including file fragment classification. As these models become more prevalent, it is crucial to understand and interpret their decision-making processes to ensure accountability ...
Narasimha Shashidhar
exaly   +2 more sources

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Byte embeddings for file fragment classification

Future Generation Computer Systems, 2022
Mehmet Engin Tozal
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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
Felix Wang, Tu-Thach Quach, James B. Aimone   +2 more
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Using NLP techniques for file fragment classification

Digital Investigation, 2012
George Mathews
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Anomaly Detection in File Fragment Classification of Image File Formats

2021
Mehdi Teimouri
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File Fragment Classification with Focus on OLE and OOXML classes

2020
Juraj Petrović, Predrag Pale
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A Byte Sequence is Worth an Image: CNN for File Fragment Classification Using Bit Shift and n-Gram Embeddings

2023
Kim-Hui Yap, Lap-Pui Chau, Kejun Wu
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GenSpec: A File Fragment Classification Approach

2020
Firas Layth Khaleel
exaly  

File fragment encoding classification—An empirical approach

Digital Investigation, 2013
Vassil Rossenou Roussev
exaly