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 301310 of 431 papers

TitleStatusHype
Towards a Robust Classifier: An MDL-Based Method for Generating Adversarial Examples0
Towards Deep Federated Defenses Against Malware in Cloud Ecosystems0
Towards Interpretable Ensemble Learning for Image-based Malware Detection0
Towards interpreting ML-based automated malware detection models: a survey0
Towards Novel Malicious Packet Recognition: A Few-Shot Learning Approach0
Towards Obfuscated Malware Detection for Low Powered IoT Devices0
Towards Poisoning of Deep Learning Algorithms with Back-gradient Optimization0
Towards Robust Real-Time Hardware-based Mobile Malware Detection using Multiple Instance Learning Formulation0
Toward the Detection of Polyglot Files0
Traffic Analytics Development Kits (TADK): Enable Real-Time AI Inference in Networking Apps0
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