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 301310 of 431 papers

TitleStatusHype
Mind Your Weight(s): A Large-scale Study on Insufficient Machine Learning Model Protection in Mobile AppsCode1
How to 0wn NAS in Your Spare TimeCode0
Analyzing CNN Based Behavioural Malware Detection Techniques on Cloud IaaS0
MDEA: Malware Detection with Evolutionary Adversarial Learning0
GLSearch: Maximum Common Subgraph Detection via Learning to Search0
Can't Boil This Frog: Robustness of Online-Trained Autoencoder-Based Anomaly Detectors to Adversarial Poisoning Attacks0
Practical Fast Gradient Sign Attack against Mammographic Image Classifier0
Interpreting Machine Learning Malware Detectors Which Leverage N-gram AnalysisCode0
Towards Deep Federated Defenses Against Malware in Cloud Ecosystems0
Malware Makeover: Breaking ML-based Static Analysis by Modifying Executable BytesCode0
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