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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 101–110 of 431 papers

TitleStatusHype
Small Effect Sizes in Malware Detection? Make Harder Train/Test Splits!—0
Discovering Malicious Signatures in Software from Structural Interactions—0
Towards an in-depth detection of malware using distributed QCNN—0
Android Malware Detection with Unbiased Confidence Guarantees—0
A Malware Classification Survey on Adversarial Attacks and Defences—0
Prompt Engineering-assisted Malware Dynamic Analysis Using GPT-4Code1
MalPurifier: Enhancing Android Malware Detection with Adversarial Purification against Evasion AttacksCode1
Explaining high-dimensional text classifiers—0
Machine learning-based malware detection for IoT devices using control-flow data—0
Enhancing Malware Detection by Integrating Machine Learning with Cuckoo Sandbox—0
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