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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 201–210 of 431 papers

TitleStatusHype
Out of Distribution Data Detection Using Dropout Bayesian Neural Networks—0
StratDef: Strategic Defense Against Adversarial Attacks in ML-based Malware Detection—0
IoT Malware Detection Architecture using a Novel Channel Boosted and Squeezed CNN—0
On The Empirical Effectiveness of Unrealistic Adversarial Hardening Against Realistic Adversarial AttacksCode0
Efficient and Robust Classification for Sparse Attacks—0
Android Malware Detection using Feature Ranking of Permissions—0
RoboMal: Malware Detection for Robot Network Systems—0
Cross-Language Binary-Source Code Matching with Intermediate Representations—0
Graph Neural Network-based Android Malware Classification with Jumping Knowledge—0
Adversarial Attacks against Windows PE Malware Detection: A Survey of the State-of-the-ArtCode1
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