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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 281–290 of 431 papers

TitleStatusHype
Learning to Search for Fast Maximum Common Subgraph Detection—0
A Novel Resampling Technique for Imbalanced Dataset Optimization—0
Assessment of the Relative Importance of different hyper-parameters of LSTM for an IDS—0
Beyond the Hype: A Real-World Evaluation of the Impact and Cost of Machine Learning-Based Malware DetectionCode0
Malware Detection using Artificial Bee Colony Algorithm—0
Towards Obfuscated Malware Detection for Low Powered IoT Devices—0
A survey on practical adversarial examples for malware classifiers—0
Being Single Has Benefits. Instance Poisoning to Deceive Malware Classifiers—0
Traffic Refinery: Cost-Aware Data Representation for Machine Learning on Network Traffic—0
Getting Passive Aggressive About False Positives: Patching Deployed Malware Detectors—0
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