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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 226–250 of 431 papers

TitleStatusHype
heterogeneous temporal graph transformer: an intelligent system for evolving android malware detectionCode1
Leveraging Uncertainty for Improved Static Malware Detection Under Extreme False Positive Constraints—0
PDF-Malware: An Overview on Threats, Detection and Evasion Attacks—0
Decision-forest voting scheme for classification of rare classes in network intrusion detection—0
Malware Analysis with Artificial Intelligence and a Particular Attention on Results Interpretability—0
Dynamic detection of mobile malware using smartphone data and machine learning—0
Android Security using NLP Techniques: A Review—0
Data Augmentation for Opcode Sequence Based Malware Detection—0
Artificial Neural Network for Cybersecurity: A Comprehensive Review—0
Evading Malware Classifiers via Monte Carlo Mutant Feature DiscoveryCode0
Towards an Automated Pipeline for Detecting and Classifying Malware through Machine Learning—0
Enhancing Robustness of Neural Networks through Fourier Stabilization—0
Multi-Task Hierarchical Learning Based Network Traffic AnalyticsCode1
MalPhase: Fine-Grained Malware Detection Using Network Flow Data—0
Learning Security Classifiers with Verified Global Robustness PropertiesCode1
Analyzing Machine Learning Approaches for Online Malware Detection in Cloud—0
Federated Learning for Malware Detection in IoT DevicesCode1
A Novel Malware Detection Mechanism based on Features Extracted from Converted Malware Binary Images—0
Early Detection of In-Memory Malicious Activity based on Run-time Environmental Features—0
Deep Learning for Android Malware Defenses: a Systematic Literature ReviewCode1
Word Embedding Techniques for Malware Evolution Detection—0
NF-GNN: Network Flow Graph Neural Networks for Malware Detection and Classification—0
Malware Classification Using Long Short-Term Memory Models—0
Malware Classification with GMM-HMM Models—0
Identification of Significant Permissions for Efficient Android Malware Detection—0
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