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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 71–80 of 431 papers

TitleStatusHype
Hyperbolic Benchmarking Unveils Network Topology-Feature Relationship in GNN PerformanceCode0
A New Formulation for Zeroth-Order Optimization of Adversarial EXEmples in Malware Detection—0
SLIFER: Investigating Performance and Robustness of Malware Detection Pipelines—0
Generative AI in Cybersecurity: A Comprehensive Review of LLM Applications and Vulnerabilities—0
Transfer Learning in Pre-Trained Large Language Models for Malware Detection Based on System Calls—0
Deep Multi-Task Learning for Malware Image Classification—0
Leveraging LSTM and GAN for Modern Malware Detection—0
Online Clustering of Known and Emerging Malware Families—0
Detecting Android Malware: From Neural Embeddings to Hands-On Validation with BERTroid—0
Explainable Malware Detection with Tailored Logic Explained Networks—0
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