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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
ORSA: Outlier Robust Stacked Aggregation for Best- and Worst-Case Approximations of Ensemble Systems\—0
Out of Distribution Data Detection Using Dropout Bayesian Neural Networks—0
Parallel Instance Filtering for Malware Detection—0
PDF-Malware: An Overview on Threats, Detection and Evasion Attacks—0
PECAN: A Deterministic Certified Defense Against Backdoor Attacks—0
PhilaeX: Explaining the Failure and Success of AI Models in Malware Detection—0
Powershell malware detection method based on features combination—0
Practical Attacks on Machine Learning: A Case Study on Adversarial Windows Malware—0
Practical Fast Gradient Sign Attack against Mammographic Image Classifier—0
Predicting Vulnerability to Malware Using Machine Learning Models: A Study on Microsoft Windows Machines—0
R2-D2: ColoR-inspired Convolutional NeuRal Network (CNN)-based AndroiD Malware Detections—0
Randomized Prediction Games for Adversarial Machine Learning—0
Recent Advances in Malware Detection: Graph Learning and Explainability—0
Recurrent Neural Network Attention Mechanisms for Interpretable System Log Anomaly Detection—0
Review of Deep Learning-based Malware Detection for Android and Windows System—0
Revisiting Static Feature-Based Android Malware Detection—0
Packet Inspection Transformer: A Self-Supervised Journey to Unseen Malware Detection with Few Samples—0
RoboMal: Malware Detection for Robot Network Systems—0
Robust Android Malware Detection System against Adversarial Attacks using Q-Learning—0
Robust and Accurate Authorship Attribution via Program Normalization—0
RoMA: Robust Malware Attribution via Byte-level Adversarial Training with Global Perturbations and Adversarial Consistency Regularization—0
SCORE: Syntactic Code Representations for Static Script Malware Detection—0
Security Evaluation of Support Vector Machines in Adversarial Environments—0
SEdroid: A Robust Android Malware Detector using Selective Ensemble Learning—0
Semantic Adversarial Deep Learning—0
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