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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 41–50 of 431 papers

TitleStatusHype
Living off the Analyst: Harvesting Features from Yara Rules for Malware Detection—0
XAI and Android Malware Models—0
On the Cost of Model-Serving Frameworks: An Experimental Evaluation—0
SCORE: Syntactic Code Representations for Static Script Malware Detection—0
Unmasking the Shadows: Pinpoint the Implementations of Anti-Dynamic Analysis Techniques in Malware Using LLM—0
Metamorphic Malware Evolution: The Potential and Peril of Large Language Models—0
Assessing the Impact of Packing on Machine Learning-Based Malware Detection and Classification Systems—0
Classification under strategic adversary manipulation using pessimistic bilevel optimisation—0
A Novel Reinforcement Learning Model for Post-Incident Malware Investigations—0
Deep Learning Based XIoT Malware Analysis: A Comprehensive Survey, Taxonomy, and Research Challenges—0
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