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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
On the impact of dataset size and class imbalance in evaluating machine-learning-based windows malware detection techniques—0
On the Security Risks of ML-based Malware Detection Systems: A Survey—0
OpCode-Based Malware Classification Using Machine Learning and Deep Learning Techniques—0
Open Image Content Disarm And Reconstruction—0
Optimization of Lightweight Malware Detection Models For AIoT Devices—0
Optimized Approaches to Malware Detection: A Study of Machine Learning and Deep Learning Techniques—0
ORSA: Outlier Robust Stacked Aggregation for Best- and Worst-Case Approximations of Ensemble Systems\—0
Out of Distribution Data Detection Using Dropout Bayesian Neural Networks—0
Parallel Instance Filtering for Malware Detection—0
PDF-Malware: An Overview on Threats, Detection and Evasion Attacks—0
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