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 81–90 of 431 papers

TitleStatusHype
A Transformer-Based Framework for Payload Malware Detection and Classification—0
A Natural Language Processing Approach for Instruction Set Architecture Identification—0
Adversarial Robustness of Deep Neural Networks: A Survey from a Formal Verification Perspective—0
A Survey on the Application of Generative Adversarial Networks in Cybersecurity: Prospective, Direction and Open Research Scopes—0
A two-steps approach to improve the performance of Android malware detectors—0
A survey on practical adversarial examples for malware classifiers—0
Analyzing Machine Learning Approaches for Online Malware Detection in Cloud—0
A Visualized Malware Detection Framework with CNN and Conditional GAN—0
Behavioral Malware Classification using Convolutional Recurrent Neural Networks—0
A Survey on Malware Detection with Graph Representation Learning—0
Show:102550
← PrevPage 9 of 44Next →

No leaderboard results yet.