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 351–360 of 431 papers

TitleStatusHype
Adversarial Samples on Android Malware Detection Systems for IoT Systems—0
Machine Learning With Feature Selection Using Principal Component Analysis for Malware Detection: A Case Study—0
A Combination Method for Android Malware Detection Based on Control Flow Graphs and Machine Learning Algorithms—0
Android Malware Detection Using Machine Learning on Image Patterns—0
Transfer Learning for Image-Based Malware ClassificationCode0
Using Deep Neural Network for Android Malware Detection—0
Android Malware Detection Using Autoencoder—0
Malware Detection Using Dynamic Birthmarks—0
A Review on The Use of Deep Learning in Android Malware Detection—0
Deep Transfer Learning for Static Malware ClassificationCode0
Show:102550
← PrevPage 36 of 44Next →

No leaderboard results yet.