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 8190 of 431 papers

TitleStatusHype
Creating Valid Adversarial Examples of MalwareCode0
Efficient Formal Safety Analysis of Neural NetworksCode0
Convolutional Neural Network for Classification of Malware Assembly CodeCode0
Crystal ball: From innovative attacks to attack effectiveness classifierCode0
Evaluating the Robustness of Adversarial Defenses in Malware Detection SystemsCode0
Adversarial Feature Selection against Evasion AttacksCode0
Beyond the Hype: A Real-World Evaluation of the Impact and Cost of Machine Learning-Based Malware DetectionCode0
ALOHA: Auxiliary Loss Optimization for Hypothesis AugmentationCode0
How to 0wn NAS in Your Spare TimeCode0
Black-Box Attacks against RNN based Malware Detection AlgorithmsCode0
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