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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 361–370 of 431 papers

TitleStatusHype
Android Malware Detection using Feature Ranking of Permissions—0
Android Malware Detection Using Machine Learning on Image Patterns—0
Android Malware Detection Using Parallel Machine Learning Classifiers—0
Android Malware Detection with Unbiased Confidence Guarantees—0
Android Security using NLP Techniques: A Review—0
An End-to-End Deep Learning Architecture for Classification of Malware’s Binary Content—0
A Neural-based Program Decompiler—0
A New Android Malware Detection Approach Using Bayesian Classification—0
A New Deep Boosted CNN and Ensemble Learning based IoT Malware Detection—0
A New Formulation for Zeroth-Order Optimization of Adversarial EXEmples in Malware Detection—0
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