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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

Showing 411420 of 431 papers

TitleStatusHype
Clipping Free Attacks Against Neural Networks0
Clustering based opcode graph generation for malware variant detection0
Coda: An End-to-End Neural Program Decompiler0
Comparison of Deep Learning and the Classical Machine Learning Algorithm for the Malware Detection0
Comprehensive evaluation of Mal-API-2019 dataset by machine learning in malware detection0
Comprehensive Survey on Adversarial Examples in Cybersecurity: Impacts, Challenges, and Mitigation Strategies0
Context-aware, Adaptive and Scalable Android Malware Detection through Online Learning (extended version)0
Contextual Weisfeiler-Lehman Graph Kernel For Malware Detection0
Counteracting Concept Drift by Learning with Future Malware Predictions0
Cross-Language Binary-Source Code Matching with Intermediate Representations0
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