Results 1 to 10 of about 489,214 (203)
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.
Yunsick Sung
exaly +4 more sources
Malware Detection Based on Code Visualization and Two-Level Classification
Information (Switzerland), 2021 Malware creators generate new malicious software samples by making minor changes in previously generated code, in order to reuse malicious code, as well as to go unnoticed from signature-based antivirus software.
Antonios Andreatos, Vassilios Moussas
exaly +4 more sources
Malware Visualization for Fine-Grained Classification
IEEE Access, 2018 Due to the rapid rise of automated tools, the number of malware variants has increased dramatically, which poses a tremendous threat to the security of the Internet.
Yong Wang, Jingfeng Xue
exaly +5 more sources
IEEE Access, 2023 In recent studies, convolutional neural networks (CNNs) are mostly used as dynamic techniques for visualization-based malware classification and detection.
Divya Meena, Mohamad Mulham Belal
exaly +3 more sources
Malware homology determination using visualized images and feature fusion [PDF]
PeerJ Computer Science, 2021 The family homology determination of malware has become a research hotspot as the number of malware variants are on the rise. However, existing studies on malware visualization only determines homology based on the global structure features of executable,
Xuejin Zhu +3 more
doaj +2 more sources
Malware Family Classification Model Based on MobileNet [PDF]
Jisuanji gongcheng, 2020 The existing malicious code classification method based on Convolutional Neural Network(CNN) has the problem of large computational resource consumption.In order to reduce the computational quantity and parameter quantity in the classification process ...
ZENG Yaqin, ZHANG Linlin, ZHANG Ruonan, YANG Bo
doaj +1 more source
MalView: Interactive Visual Analytics for Comprehending Malware Behavior
IEEE Access, 2022 Malicious applications are usually comprehended through two major techniques, namely static and dynamic analyses. Through static analysis, a given malicious program is parsed, and some representative artifacts (e.g., control-flow graphs) are produced ...
Huyen N. Nguyen +5 more
doaj +1 more source
IIoT Malware Detection Using Edge Computing and Deep Learning for Cybersecurity in Smart Factories
Applied Sciences, 2022 The smart factory environment has been transformed into an Industrial Internet of Things (IIoT) environment, which is an interconnected and open approach.
Ho-myung Kim, Kyung-ho Lee
doaj +1 more source
An Efficient DenseNet-Based Deep Learning Model for Malware Detection
Entropy, 2021 Recently, there has been a huge rise in malware growth, which creates a significant security threat to organizations and individuals. Despite the incessant efforts of cybersecurity research to defend against malware threats, malware developers discover ...
Jeyaprakash Hemalatha +4 more
doaj +1 more source
Intelligent Vision-Based Malware Detection and Classification Using Deep Random Forest Paradigm
IEEE Access, 2020 Malware is a rapidly increasing menace to modern computing. Malware authors continually incorporate various sophisticated features like code obfuscations to create malware variants and elude detection by existing malware detection systems.
S. Abijah Roseline +3 more
doaj +1 more source