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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

Showing 161170 of 431 papers

TitleStatusHype
Mask Off: Analytic-based Malware Detection By Transfer Learning and Model Personalization0
Clustering based opcode graph generation for malware variant detection0
Reliable Malware Analysis and Detection using Topology Data AnalysisCode0
UniASM: Binary Code Similarity Detection without Fine-tuningCode1
Flexible Android Malware Detection Model based on Generative Adversarial Networks with Code Tensor0
The State-of-the-Art in AI-Based Malware Detection Techniques: A Review0
Avast-CTU Public CAPE DatasetCode1
Instance Attack:An Explanation-based Vulnerability Analysis Framework Against DNNs for Malware Detection0
Traffic Analytics Development Kits (TADK): Enable Real-Time AI Inference in Networking Apps0
Self-Supervised Vision Transformers for Malware DetectionCode1
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