SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 371–380 of 431 papers

TitleStatusHype
Efficient Concept Drift Handling for Batch Android Malware Detection ModelsCode0
Malware Detection based on API callsCode0
Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust Deep LearningCode0
Interpreting Machine Learning Malware Detectors Which Leverage N-gram AnalysisCode0
Dynamic Malware Analysis with Feature Engineering and Feature LearningCode0
pAElla: Edge-AI based Real-Time Malware Detection in Data CentersCode0
When a RF Beats a CNN and GRU, Together -- A Comparison of Deep Learning and Classical Machine Learning Approaches for Encrypted Malware Traffic ClassificationCode0
Adversarially Robust Learning with Optimal Transport Regularized DivergencesCode0
EvadeDroid: A Practical Evasion Attack on Machine Learning for Black-box Android Malware DetectionCode0
Robust Neural Malware Detection Models for Emulation Sequence LearningCode0
Show:102550
← PrevPage 38 of 44Next →

No leaderboard results yet.