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Malware Detection

Malware Detection is a significant part of endpoint security including workstations, servers, cloud instances, and mobile devices. Malware Detection is used to detect and identify malicious activities caused by malware. With the increase in the variety of malware activities on CMS based websites such as malicious malware redirects on WordPress site (Aka, WordPress Malware Redirect Hack) where the site redirects to spam, being the most widespread, the need for automatic detection and classifier amplifies as well. The signature-based Malware Detection system is commonly used for existing malware that has a signature but it is not suitable for unknown malware or zero-day malware

Source: The Threat of Adversarial Attacks on Machine Learning in Network Security - A Survey

Papers

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Showing 321–330 of 431 papers

TitleStatusHype
An MDL-Based Classifier for Transactional Datasets with Application in Malware Detection—0
A Hierarchical Convolutional Neural Network for Malware Classification—0
COPYCAT: Practical Adversarial Attacks on Visualization-Based Malware Detection—0
I-MAD: Interpretable Malware Detector Using Galaxy Transformer—0
Effectiveness of Adversarial Examples and Defenses for Malware Classification—0
SEdroid: A Robust Android Malware Detector using Selective Ensemble Learning—0
On Defending Against Label Flipping Attacks on Malware Detection Systems—0
Similarity-based Android Malware Detection Using Hamming Distance of Static Binary Features—0
New Era of Deeplearning-Based Malware Intrusion Detection: The Malware Detection and Prediction Based On Deep Learning—0
Dynamic Malware Analysis with Feature Engineering and Feature LearningCode0
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