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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 421–430 of 431 papers

TitleStatusHype
Malware Makeover: Breaking ML-based Static Analysis by Modifying Executable BytesCode0
Statistical Estimation of Malware Detection Metrics in the Absence of Ground TruthCode0
Malware Classification using Deep Learning based Feature Extraction and Wrapper based Feature Selection TechniqueCode0
Imbalanced malware classification: an approach based on dynamic classifier selectionCode0
Improving Adversarial Robustness in Android Malware Detection by Reducing the Impact of Spurious CorrelationsCode0
Stealing and Evading Malware Classifiers and Antivirus at Low False Positive ConditionsCode0
Improving Malware Detection Accuracy by Extracting Icon InformationCode0
Sequential Embedding-based Attentive (SEA) classifier for malware classificationCode0
Orthrus: A Bimodal Learning Architecture for Malware ClassificationCode0
Accelerating Malware Classification: A Vision Transformer SolutionCode0
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