Results 21 to 30 of about 529,627 (283)
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 +3 more
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Vietnam Journal of Computer Science, 2023 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 high-entropy file fragments.
Kristian Skračić +2 more
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Ionic concentration in periradicular medium after dissolution of endodontic file fragments: an in vitro study [PDF]
Brazilian Oral Research, 2022 The aim of this study was to obtain ionic quantification in periradicular medium after diffusion tests of the solution used inside root canals during the electrochemical dissolution of endodontic file fragments and the NiTi-containing dissolution product
Fabiola ORMIGA +9 more
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File Fragmentation in the Wild: a Privacy-Friendly Approach [PDF]
2019 IEEE International Workshop on Information Forensics and Security (WIFS), 2019 Digital forensic tooling should be based on reference data. Such reference data can be gathered by measuring a baseline, e.g. from volunteers. However, the privacy provisions in digital forensics tools are typically tailored for criminal investigations. This is not sufficient to ensure privacy obligations towards volunteer participants.
van der Meer, Vincent +5 more
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Syntactical method for reconstructing highly fragmented OOXML files
Радіоелектронні і комп'ютерні системи, 2023 A common task in computer forensics is to recover files that lack file system metadata. In the case of searching for file fragments in unallocated space, file carving is the most often used method, which is ideal for unfragmented data.
Maksym Boiko, Viacheslav Moskalenko
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A contemporary investigation of NTFS file fragmentation
Forensic Science International: Digital Investigation, 2021 There is a significant amount of research in digital forensics into analyzing file fragments or reconstructing fragmented data. At the same time, there are no recent measurements of fragmentation on current, in-use computer systems. To close this gap, we have analyzed file fragmentation from a corpus of 220 privately owned Windows laptops.We provide a ...
van der Meer, Vincent +2 more
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Entropy Based Method for Malicious File Detection
JOIV: International Journal on Informatics Visualization, 2022 Ransomware is by no means a recent invention, having existed as far back as 1989, yet it still poses a real threat in the 21st century. Given the increasing number of computer users in recent years, this threat will only continue to grow, affecting more ...
Muhammad Edzuan Zainodin +3 more
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SIFT – File Fragment Classification Without Metadata
2023 3rd International Conference on Computing and Information Technology (ICCIT), 2023 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 developing methods to classify file fragments. In this research, a novel sifting approach, named SIFT (Sifting File Types), is proposed.
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Dew Computing and Asymmetric Security Framework for Big Data File Sharing
Information, 2020 Due to the advancement of technology, devices generate huge working files at a rapid rate. These data, which are of considerable scale and are created very fast, can be called big data. Keeping such files in one storage device is impossible. Therefore, a
Parinya Suwansrikham +3 more
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HTTP adaptive streaming with media fragment URIs [PDF]
, 2011 HTTP adaptive streaming was introduced with the general idea that user agents interpret a manifest file (describing different representations and segments of the media); where-after they retrieve the media content using sequential HTTP progressive ...
Mannens, Erik +3 more
core +1 more source