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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

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Showing 91–100 of 431 papers

TitleStatusHype
Comprehensive evaluation of Mal-API-2019 dataset by machine learning in malware detection—0
Improving Android Malware Detection Through Data Augmentation Using Wasserstein Generative Adversarial Networks—0
How to Train your Antivirus: RL-based Hardening through the Problem-SpaceCode0
Use of Multi-CNNs for Section Analysis in Static Malware Detection—0
Weakly Supervised Anomaly Detection via Knowledge-Data Alignment—0
Unraveling the Key of Machine Learning Solutions for Android Malware Detection—0
Evading Deep Learning-Based Malware Detectors via Obfuscation: A Deep Reinforcement Learning Approach—0
ActDroid: An active learning framework for Android malware detection—0
MORPH: Towards Automated Concept Drift Adaptation for Malware Detection—0
Malware Detection in IOT Systems Using Machine Learning Techniques—0
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