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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 111–120 of 431 papers

TitleStatusHype
An investigation of the classifiers to detect android malicious apps—0
A Hierarchical Convolutional Neural Network for Malware Classification—0
Cross-Language Binary-Source Code Matching with Intermediate Representations—0
An investigation of a deep learning based malware detection system—0
Counteracting Concept Drift by Learning with Future Malware Predictions—0
A New Malware Detection System Using a High Performance-ELM method—0
A New Formulation for Zeroth-Order Optimization of Adversarial EXEmples in Malware Detection—0
Contextual Weisfeiler-Lehman Graph Kernel For Malware Detection—0
Context-aware, Adaptive and Scalable Android Malware Detection through Online Learning (extended version)—0
A New Deep Boosted CNN and Ensemble Learning based IoT Malware Detection—0
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