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 31–40 of 431 papers

TitleStatusHype
Federated Learning for Malware Detection in IoT DevicesCode1
Avast-CTU Public CAPE DatasetCode1
Classifying Sequences of Extreme Length with Constant Memory Applied to Malware DetectionCode1
Continuous Learning for Android Malware DetectionCode1
Dataset Optimization Strategies for MalwareTraffic DetectionCode1
Decoding the Secrets of Machine Learning in Malware Classification: A Deep Dive into Datasets, Feature Extraction, and Model PerformanceCode1
MalPurifier: Enhancing Android Malware Detection with Adversarial Purification against Evasion AttacksCode1
Efficient Query-Based Attack against ML-Based Android Malware Detection under Zero Knowledge SettingCode1
heterogeneous temporal graph transformer: an intelligent system for evolving android malware detectionCode1
Semantic-preserving Reinforcement Learning Attack Against Graph Neural Networks for Malware DetectionCode1
Show:102550
← PrevPage 4 of 44Next →

No leaderboard results yet.