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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 161–170 of 431 papers

TitleStatusHype
Generative AI-Based Effective Malware Detection for Embedded Computing Systems—0
Effectiveness of Adversarial Examples and Defenses for Malware Classification—0
Effectiveness of Moving Target Defenses for Adversarial Attacks in ML-based Malware Detection—0
Efficient and Robust Classification for Sparse Attacks—0
Efficient Attack Detection in IoT Devices using Feature Engineering-Less Machine Learning—0
A Survey on the Application of Generative Adversarial Networks in Cybersecurity: Prospective, Direction and Open Research Scopes—0
A Transformer-Based Framework for Payload Malware Detection and Classification—0
Efficient Malware Analysis Using Metric Embeddings—0
Efficient Malware Detection with Optimized Learning on High-Dimensional Features—0
A Modern Analysis of Aging Machine Learning Based IoT Cybersecurity Methods—0
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