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 261–270 of 431 papers

TitleStatusHype
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
Show:102550
← PrevPage 27 of 44Next →

No leaderboard results yet.