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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

Showing 381390 of 431 papers

TitleStatusHype
apk2vec: Semi-supervised multi-view representation learning for profiling Android applications0
Applications of Positive Unlabeled (PU) and Negative Unlabeled (NU) Learning in Cybersecurity0
A Review of Computer Vision Methods in Network Security0
A Review on The Use of Deep Learning in Android Malware Detection0
Artificial Neural Network for Cybersecurity: A Comprehensive Review0
A short review on Applications of Deep learning for Cyber security0
Transferable Cost-Aware Security Policy Implementation for Malware Detection Using Deep Reinforcement Learning0
Assessing Cyclostationary Malware Detection via Feature Selection and Classification0
Assessing the Impact of Packing on Machine Learning-Based Malware Detection and Classification Systems0
Assessment of the Relative Importance of different hyper-parameters of LSTM for an IDS0
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