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 311320 of 431 papers

TitleStatusHype
Interpreting Machine Learning Malware Detectors Which Leverage N-gram AnalysisCode0
Practical Fast Gradient Sign Attack against Mammographic Image Classifier0
Towards Deep Federated Defenses Against Malware in Cloud Ecosystems0
Malware Makeover: Breaking ML-based Static Analysis by Modifying Executable BytesCode0
Towards a Robust Classifier: An MDL-Based Method for Generating Adversarial Examples0
Coda: An End-to-End Neural Program Decompiler0
DL-Droid: Deep learning based android malware detection using real devices0
Classification with Costly Features in Hierarchical Deep SetsCode0
There is Limited Correlation between Coverage and Robustness for Deep Neural Networks0
The Naked Sun: Malicious Cooperation Between Benign-Looking Processes0
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