Results 21 to 30 of about 1,811,594 (209)
An Analysis of Android Malware Classification Services. [PDF]
Sensors (Basel), 2021 The increasing number of Android malware forced antivirus (AV) companies to rely on automated classification techniques to determine the family and class of suspicious samples. The research community relies heavily on such labels to carry out prevalence studies of the threat ecosystem and to build datasets that are used to validate and benchmark novel ...
Rashed M, Suarez-Tangil G.
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Malware-on-the-Brain: Illuminating Malware Byte Codes With Images for Malware Classification
IEEE Transactions on Computers, 2023 Malware is a piece of software that was written with the intent of doing harm to data, devices, or people. Since a number of new malware variants can be generated by reusing codes, malware attacks can be easily launched and thus become common in recent years, incurring huge losses in businesses, governments, financial institutes, health providers, etc.
Fangtian Zhong +5 more
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Applied Sciences, 2020 Traditional malware classification relies on known malware types and significantly large datasets labeled manually which limits its ability to recognize new malware classes.
Zhijie Tang, Peng Wang, Junfeng Wang
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On the effectiveness of binary emulation in malware classification
Journal of Information Security and Applications, 2022 Malware authors are continuously evolving their code base to include counter-analysis methods that can significantly hinder their detection and blocking. While the execution of malware in a sandboxed environment may provide a lot of insightful feedback about what the malware actually does in a machine, anti-virtualisation and hooking evasion methods ...
Vouvoutsis, Vasilis +2 more
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IEEE Access, 2023 In recent studies, convolutional neural networks (CNNs) are mostly used as dynamic techniques for visualization-based malware classification and detection.
Mohamad Mulham Belal +1 more
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Frontiers in Plant Science, 2023 Due to developments in science and technology, the field of plant protection and the information industry have become increasingly integrated, which has resulted in the creation of plant protection information systems.
Zhiguo Chen +5 more
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Deep learning based Sequential model for malware analysis using Windows exe API Calls [PDF]
PeerJ Computer Science, 2020 Malware development has seen diversity in terms of architecture and features. This advancement in the competencies of malware poses a severe threat and opens new research dimensions in malware detection.
Ferhat Ozgur Catak +3 more
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Multiple instance learning for malware classification [PDF]
Expert Systems with Applications, 2018 This work addresses classification of unknown binaries executed in sandbox by modeling their interaction with system resources (files, mutexes, registry keys and communication with servers over the network) and error messages provided by the operating system, using vocabulary-based method from the multiple instance learning paradigm.
Jan Stiborek +2 more
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Mathematics, 2022 The rapid increase of malware attacks has become one of the main threats to computer security. Finding the best way to detect malware has become a critical task in cybersecurity. Previous work shows that machine learning approaches could be a solution to
Wei-Cheng Lin, Yi-Ren Yeh
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Mathematics, 2020 The importance of cybersecurity has recently been increasing. A malware coder writes malware into normal executable files. A computer is more likely to be infected by malware when users have easy access to various executables.
Sejun Jang, Shuyu Li, Yunsick Sung
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