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

Showing 6170 of 431 papers

TitleStatusHype
Android Malware Detection Based on RGB Images and Multi-feature Fusion0
Improving Adversarial Robustness in Android Malware Detection by Reducing the Impact of Spurious CorrelationsCode0
Obfuscated Memory Malware Detection0
Natural Language Outlines for Code: Literate Programming in the LLM Era0
A Survey of Malware Detection Using Deep Learning0
Explainable AI-based Intrusion Detection System for Industry 5.0: An Overview of the Literature, associated Challenges, the existing Solutions, and Potential Research Directions0
A Survey on the Application of Generative Adversarial Networks in Cybersecurity: Prospective, Direction and Open Research Scopes0
Detecting new obfuscated malware variants: A lightweight and interpretable machine learning approach0
On the Abuse and Detection of Polyglot Files0
Unsupervised representation learning with Hebbian synaptic and structural plasticity in brain-like feedforward neural networks0
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