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

Showing 2130 of 431 papers

TitleStatusHype
Multi-Task Hierarchical Learning Based Network Traffic AnalyticsCode1
Learning Security Classifiers with Verified Global Robustness PropertiesCode1
Federated Learning for Malware Detection in IoT DevicesCode1
Deep Learning for Android Malware Defenses: a Systematic Literature ReviewCode1
MalNet: A Large-Scale Image Database of Malicious SoftwareCode1
Malware Detection Using Frequency Domain-Based Image Visualization and Deep LearningCode1
Classifying Sequences of Extreme Length with Constant Memory Applied to Malware DetectionCode1
Against All Odds: Winning the Defense Challenge in an Evasion Competition with DiversificationCode1
Data Augmentation Based Malware Detection using Convolutional Neural NetworksCode1
Dataset Optimization Strategies for MalwareTraffic DetectionCode1
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