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 131140 of 431 papers

TitleStatusHype
Coda: An End-to-End Neural Program Decompiler0
A Neural-based Program Decompiler0
Clustering based opcode graph generation for malware variant detection0
Clipping Free Attacks Against Neural Networks0
An End-to-End Deep Learning Architecture for Classification of Malware’s Binary Content0
Clipping free attacks against artificial neural networks0
A Feature Set of Small Size for the PDF Malware Detection0
Adaptive and Scalable Android Malware Detection through Online Learning0
Classification under strategic adversary manipulation using pessimistic bilevel optimisation0
Certified Adversarial Robustness of Machine Learning-based Malware Detectors via (De)Randomized Smoothing0
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