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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 71–80 of 431 papers

TitleStatusHype
A two-steps approach to improve the performance of Android malware detectors—0
Android Malware Detection using Feature Ranking of Permissions—0
Android Malware Detection using Deep Learning on API Method Sequences—0
Adversarial Samples on Android Malware Detection Systems for IoT Systems—0
Android Malware Detection Using Autoencoder—0
Android Malware Detection Based on RGB Images and Multi-feature Fusion—0
ActDroid: An active learning framework for Android malware detection—0
A Natural Language Processing Approach to Malware Classification—0
A Natural Language Processing Approach for Instruction Set Architecture Identification—0
Adversarial Robustness of Deep Neural Networks: A Survey from a Formal Verification Perspective—0
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