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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 171–180 of 431 papers

TitleStatusHype
A Modern Analysis of Aging Machine Learning Based IoT Cybersecurity Methods—0
Empirical Quantification of Spurious Correlations in Malware Detection—0
Design of secure and robust cognitive system for malware detection—0
Enhanced Attacks on Defensively Distilled Deep Neural Networks—0
Defending against Adversarial Malware Attacks on ML-based Android Malware Detection Systems—0
A Review of Computer Vision Methods in Network Security—0
Enhancing Malware Detection by Integrating Machine Learning with Cuckoo Sandbox—0
Enhancing Robustness of Neural Networks through Fourier Stabilization—0
Behavioral Malware Classification using Convolutional Recurrent Neural Networks—0
Explainable Malware Detection with Tailored Logic Explained Networks—0
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