Results 21 to 30 of about 142,585 (248)

Adversarial Shadows in Digital Forensics: New Insights Into File Fragment Classification Vulnerabilities and Defenses

IEEE Access
The paper is a comprehensive survey of adversarial attacks on file fragment classification (FFC) models - a relatively unexplored area in digital forensics, given the increasing application of machine learning techniques.
Teena Mary, C. S. Sreeja
doaj   +2 more sources

File Fragment Classification Using Grayscale Image Conversion and Deep Learning in Digital Forensics [PDF]

2018 IEEE Security and Privacy Workshops (SPW), 2018
File fragment classification is an important step in digital forensics. The most popular method is based on traditional machine learning by extracting features like N-gram, Shannon entropy or Hamming weights. However, these features are far from enough to classify file fragments.
Qian Chen, Qing Liao, Zoe L. Jiang, Junbin Fang, Siu‐Ming Yiu, Guikai Xi, Rong Li, Zhengzhong Yi, Xuan Wang, Lucas C. K. Hui, Dong Liu, En Zhang   +11 more
openalex   +2 more sources

Transformer-Based File Fragment Type Classification for File Carving in Digital Forensics

European Conference on Cyber Warfare and Security
The recovery and reconstruction of fragmented data is a critical challenge in digital forensics, particularly when dealing with incomplete, corrupted, or partially deleted files in large-scale cybercrime investigations. Accurate classification of file fragment types is essential for reconstructing critical evidence, especially in environments ...
Andrey Guzhov, Christoph Tobias Wirth
openalex   +3 more sources

A File Fragment Classification Method Based on Grayscale Image

Journal of Computers, 2014
File fragment classification is an important and difficult problem in digital forensics. Previous works in this area mainly relied on specific byte sequences in file headers and footers, or statistical analysis and machine learning algorithms on data from the middle of the file.
Tantan Xu, Ming Xu, Yizhi Ren, Jian Xu, Haiping Zhang, Ning Zheng   +5 more
openalex   +2 more sources

The file fragment classification problem : a combined neural network and linear programming discriminant model approach

, 2013
The increased use of digital media to store legal, as well as illegal data, has created the need for specialized tools that can monitor, control and even recover this data. An important task in computer forensics and security is to identify the true le type to which a computer le or computer le fragment belongs.
Erich Feodor Wilgenbus
openalex   +3 more sources

Support Vector Machines-based classification of video file fragments

Journal of the Korea Academia-Industrial cooperation Society, 2015
Hyun-Suk Kang, Youngseok Lee
openalex   +3 more sources

Light-Weight File Fragments Classification Using Depthwise Separable Convolutions

, 2022
Kunwar Muhammed Saaim, Muhamad Felemban, Saleh M. Al‐Saleh, Ahmad Almulhem   +3 more
openalex   +3 more sources

Gerstmann-Sträussler-Scheinker disease revisited: accumulation of covalently-linked multimers of internal prion protein fragments [PDF]

, 2019
Despite their phenotypic heterogeneity, most human prion diseases belong to two broadly defined groups: Creutzfeldt-Jakob disease (CJD) and Gerstmann-Sträussler-Scheinker disease (GSS).
Cali, Ignazio, Cracco, Laura, Gambetti, Pierluigi, Ghetti, Bernardino, Lavrich, Jody, Nemani, Satish K., Notari, Silvio, Surewicz, Witold K., Xiao, Xiangzhu   +8 more
core   +1 more source

o-glasses: Visualizing X86 Code From Binary Using a 1D-CNN

IEEE Access, 2020
Malicious document files used in targeted attacks often contain a small program called shellcode. It is often hard to prepare a runnable environment for dynamic analysis of these document files because they exploit specific vulnerabilities.
Yuhei Otsubo, Akira Otsuka, Mamoru Mimura, Takeshi Sakaki   +3 more
doaj   +1 more source

MMsPred: a bioactivity and toxicology predictive system [PDF]

, 2010
In the last decade, the development and use of new methods in combinatorial chemistry and high-throughput screening has dramatically increased the number of known biologically active compounds.
Joel Masciocchi, Luca Pani, Luca Pireddu, Matteo Floris, Patricia Rodriguez-Tome, Piergiorgio Palla, Ricardo Medda   +6 more
core   +2 more sources