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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 371–380 of 431 papers

TitleStatusHype
A New Malware Detection System Using a High Performance-ELM method—0
An investigation of a deep learning based malware detection system—0
An investigation of the classifiers to detect android malicious apps—0
An MDL-Based Classifier for Transactional Datasets with Application in Malware Detection—0
A Non-Intrusive Machine Learning Solution for Malware Detection and Data Theft Classification in Smartphones—0
A Novel Approach to Malicious Code Detection Using CNN-BiLSTM and Feature Fusion—0
A novel DL approach to PE malware detection: exploring Glove vectorization, MCC_RCNN and feature fusion—0
A Novel Malware Detection Mechanism based on Features Extracted from Converted Malware Binary Images—0
A Novel Reinforcement Learning Model for Post-Incident Malware Investigations—0
A Novel Resampling Technique for Imbalanced Dataset Optimization—0
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