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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

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Showing 131–140 of 431 papers

TitleStatusHype
A Natural Language Processing Approach to Malware Classification—0
Review of Deep Learning-based Malware Detection for Android and Windows System—0
From ChatGPT to ThreatGPT: Impact of Generative AI in Cybersecurity and Privacy—0
Creating Valid Adversarial Examples of MalwareCode0
On building machine learning pipelines for Android malware detection: a procedural survey of practices, challenges and opportunities—0
A Survey on Cross-Architectural IoT Malware Threat Hunting—0
Interpreting GNN-based IDS Detections Using Provenance Graph Structural Features—0
Recasting Self-Attention with Holographic Reduced RepresentationsCode1
FGAM:Fast Adversarial Malware Generation Method Based on Gradient Sign—0
How Deep Learning Sees the World: A Survey on Adversarial Attacks & Defenses—0
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