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 121130 of 431 papers

TitleStatusHype
Agent-based Vs Agent-less Sandbox for Dynamic Behavioral Analysis0
Data Augmentation for Opcode Sequence Based Malware Detection0
Feature Extraction for Novelty Detection in Network Traffic0
Deceiving End-to-End Deep Learning Malware Detectors using Adversarial Examples0
Decentralised firewall for malware detection0
Decision-forest voting scheme for classification of rare classes in network intrusion detection0
Comprehensive Survey on Adversarial Examples in Cybersecurity: Impacts, Challenges, and Mitigation Strategies0
Comprehensive evaluation of Mal-API-2019 dataset by machine learning in malware detection0
A New Android Malware Detection Approach Using Bayesian Classification0
Comparison of Deep Learning and the Classical Machine Learning Algorithm for the Malware Detection0
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