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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 351–360 of 431 papers

TitleStatusHype
A Multi-view Context-aware Approach to Android Malware Detection and Malicious Code Localization—0
Analysing Safety Risks in LLMs Fine-Tuned with Pseudo-Malicious Cyber Security Data—0
Analysis of Bayesian Classification based Approaches for Android Malware Detection—0
Analyzing CNN Based Behavioural Malware Detection Techniques on Cloud IaaS—0
Analyzing Machine Learning Approaches for Online Malware Detection in Cloud—0
A Natural Language Processing Approach for Instruction Set Architecture Identification—0
A Natural Language Processing Approach to Malware Classification—0
Android Malware Detection Based on RGB Images and Multi-feature Fusion—0
Android Malware Detection Using Autoencoder—0
Android Malware Detection using Deep Learning on API Method Sequences—0
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