Results 21 to 30 of about 2,185,837 (169)
Self-Attentive Models for Real-Time Malware Classification
IEEE Access, 2022 Malware classification is a critical task in cybersecurity, as it offers insights into the threats that malware poses to the victim device and helps in the design of countermeasures.
Qikai Lu +3 more
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A Hybrid Approach for Android Malware Detection and Family Classification.
International Journal of Interactive Multimedia and Artificial Intelligence, 2021 With the increase in the popularity of mobile devices, malicious applications targeting Android platform have greatly increased. Malware is coded so prudently that it has become very complicated to identify.
Meghna Dhalaria, Ekta Gandotra
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Learning and classification of malware behavior
, 2022 S.108-125Malicious software in form of Internet worms, computer viruses, and Trojan horses poses a major threat to the security of networked systems. The diversity and amount of its variants severely undermine the effectiveness of classical signature ...
Düssel, P. +4 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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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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A Classification System for Visualized Malware Based on Multiple Autoencoder Models
IEEE Access, 2021 In this paper, we propose a classification system that uses multiple autoencoder models for identifying malware images. It is crucial to accurately classify malware before we can deploy appropriate countermeasures to prevent them from spreading.
Jongkwan Lee, Jongdeog Lee
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A deep learning framework for malware classification [PDF]
, 2020 Copyright © 2020, IGI Global. In this article, the authors propose a deep learning framework for malware classification. There has been a huge increase in the volume of malware in recent years which poses serious security threats to financial ...
Rochan, Mrigank +11 more
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IEEE Access, 2021 Numerous metamorphic and polymorphic malicious variants are generated automatically on a daily basis. In order to do that, malware vendors employ mutation engines that transform the code of a malicious program while retaining its functionality, aiming to
Ron Korine, Danny Hendler
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AFAgarap/malware-classification v0.1-alpha
, 2017 <p>Code implementation of "Towards Building an Intelligent Anti-Malware System: A Deep Learning Approach using Support Vector Machine (SVM) for Malware Classification"</p ...
Abien Fred Agarap
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Malware classification dataset, code and results
, 2023 Malware classification dataset, code and ...
Md Ashikur Rahman
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