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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 1–10 of 431 papers

TitleStatusHype
Efficient Malware Detection with Optimized Learning on High-Dimensional Features—0
Empirical Quantification of Spurious Correlations in Malware Detection—0
Network Threat Detection: Addressing Class Imbalanced Data with Deep Forest—0
EMBER2024 -- A Benchmark Dataset for Holistic Evaluation of Malware ClassifiersCode2
System Calls for Malware Detection and Classification: Methodologies and Applications—0
Dynamic Malware Classification of Windows PE Files using CNNs and Greyscale Images Derived from Runtime API Call Argument Conversion—0
LAMDA: A Longitudinal Android Malware Benchmark for Concept Drift AnalysisCode1
Adapting Novelty towards Generating Antigens for Antivirus systems—0
MADCAT: Combating Malware Detection Under Concept Drift with Test-Time Adaptation—0
Malware families discovery via Open-Set Recognition on Android manifest permissions—0
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