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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 251–275 of 431 papers

TitleStatusHype
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
MalPhase: Fine-Grained Malware Detection Using Network Flow Data—0
Analyzing Machine Learning Approaches for Online Malware Detection in Cloud—0
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
Word Embedding Techniques for Malware Evolution Detection—0
NF-GNN: Network Flow Graph Neural Networks for Malware Detection and Classification—0
Malware Classification with GMM-HMM Models—0
Malware Classification Using Long Short-Term Memory Models—0
Detection of Malicious Android Applications: Classical Machine Learning vs. Deep Neural Network Integrated with Clustering—0
Virus-MNIST: A Benchmark Malware Dataset—0
Identification of Significant Permissions for Efficient Android Malware Detection—0
Collective Intelligence: Decentralized Learning for Android Malware Detection in IoT with Blockchain—0
A Non-Intrusive Machine Learning Solution for Malware Detection and Data Theft Classification in Smartphones—0
Robust Android Malware Detection System against Adversarial Attacks using Q-Learning—0
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