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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 171–180 of 431 papers

TitleStatusHype
Design of secure and robust cognitive system for malware detection—0
Practical Attacks on Machine Learning: A Case Study on Adversarial Windows Malware—0
AI-based Malware and Ransomware Detection Models—0
PhilaeX: Explaining the Failure and Success of AI Models in Malware Detection—0
Parallel Instance Filtering for Malware Detection—0
Multifamily Malware Models—0
Malware Detection and Prevention using Artificial Intelligence Techniques—0
Adversarial Robustness of Deep Neural Networks: A Survey from a Formal Verification Perspective—0
When a RF Beats a CNN and GRU, Together -- A Comparison of Deep Learning and Classical Machine Learning Approaches for Encrypted Malware Traffic ClassificationCode0
On the impact of dataset size and class imbalance in evaluating machine-learning-based windows malware detection techniques—0
Show:102550
← PrevPage 18 of 44Next →

No leaderboard results yet.