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 251–260 of 431 papers

TitleStatusHype
FGAM:Fast Adversarial Malware Generation Method Based on Gradient Sign—0
Flexible Android Malware Detection Model based on Generative Adversarial Networks with Code Tensor—0
Fraternal Twins: Unifying Attacks on Machine Learning and Digital Watermarking—0
From ChatGPT to ThreatGPT: Impact of Generative AI in Cybersecurity and Privacy—0
Generative Adversarial Networks and Image-Based Malware Classification—0
Generative Adversarial Networks for Malware Detection: a Survey—0
Generative AI in Cybersecurity: A Comprehensive Review of LLM Applications and Vulnerabilities—0
Getting Passive Aggressive About False Positives: Patching Deployed Malware Detectors—0
Graph Neural Network-based Android Malware Classification with Jumping Knowledge—0
HAPSSA: Holistic Approach to PDF Malware Detection Using Signal and Statistical Analysis—0
Show:102550
← PrevPage 26 of 44Next →

No leaderboard results yet.