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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 421–430 of 431 papers

TitleStatusHype
Data Augmentation for Opcode Sequence Based Malware Detection—0
Deceiving End-to-End Deep Learning Malware Detectors using Adversarial Examples—0
Decentralised firewall for malware detection—0
Decision-forest voting scheme for classification of rare classes in network intrusion detection—0
Decoding Android Malware with a Fraction of Features: An Attention-Enhanced MLP-SVM Approach—0
Deep Image: A precious image based deep learning method for online malware detection in IoT Environment—0
Deep Learning Based XIoT Malware Analysis: A Comprehensive Survey, Taxonomy, and Research Challenges—0
Deep Multi-Task Learning for Malware Image Classification—0
Defending against Adversarial Malware Attacks on ML-based Android Malware Detection Systems—0
Design of secure and robust cognitive system for malware detection—0
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