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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
Analyzing Machine Learning Approaches for Online Malware Detection in Cloud—0
Contextual Weisfeiler-Lehman Graph Kernel For Malware Detection—0
A Survey on Malware Detection with Graph Representation Learning—0
A New Formulation for Zeroth-Order Optimization of Adversarial EXEmples in Malware Detection—0
A Survey on Cross-Architectural IoT Malware Threat Hunting—0
Analyzing CNN Based Behavioural Malware Detection Techniques on Cloud IaaS—0
Cross-Language Binary-Source Code Matching with Intermediate Representations—0
An investigation of a deep learning based malware detection system—0
Adversarial Perturbations Against Deep Neural Networks for Malware Classification—0
Investigating Feature and Model Importance in Android Malware Detection: An Implemented Survey and Experimental Comparison of ML-Based Methods—0
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