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 341350 of 431 papers

TitleStatusHype
Can Machine Learning Model with Static Features be Fooled: an Adversarial Machine Learning Approach0
Malware Evasion Attack and Defense0
Malware Detection using Machine Learning and Deep Learning0
Understanding the efficacy, reliability and resiliency of computer vision techniques for malware detection and future research directions0
ALOHA: Auxiliary Loss Optimization for Hypothesis AugmentationCode0
Agent-based Vs Agent-less Sandbox for Dynamic Behavioral Analysis0
Examining Adversarial Learning against Graph-based IoT Malware Detection Systems0
Adversarial Samples on Android Malware Detection Systems for IoT Systems0
Machine Learning With Feature Selection Using Principal Component Analysis for Malware Detection: A Case Study0
A Combination Method for Android Malware Detection Based on Control Flow Graphs and Machine Learning Algorithms0
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