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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 51–60 of 431 papers

TitleStatusHype
Feature Extraction for Novelty Detection in Network Traffic—0
A New Android Malware Detection Approach Using Bayesian Classification—0
A Neural-based Program Decompiler—0
Adaptive and Scalable Android Malware Detection through Online Learning—0
An End-to-End Deep Learning Architecture for Classification of Malware’s Binary Content—0
A New Formulation for Zeroth-Order Optimization of Adversarial EXEmples in Malware Detection—0
A Feature Set of Small Size for the PDF Malware Detection—0
An investigation of a deep learning based malware detection system—0
A Combination Method for Android Malware Detection Based on Control Flow Graphs and Machine Learning Algorithms—0
Machine Learning for Detecting Malware in PE Files—0
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