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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 271–280 of 431 papers

TitleStatusHype
Image-Based Malware Classification Using QR and Aztec Codes—0
Improving Android Malware Detection Through Data Augmentation Using Wasserstein Generative Adversarial Networks—0
Improving Radioactive Material Localization by Leveraging Cyber-Security Model Optimizations—0
"Influence Sketching": Finding Influential Samples In Large-Scale Regressions—0
Instance Attack:An Explanation-based Vulnerability Analysis Framework Against DNNs for Malware Detection—0
Integrating Explainable AI for Effective Malware Detection in Encrypted Network Traffic—0
Intelligent Systems Design for Malware Classification Under Adversarial Conditions—0
Interpreting GNN-based IDS Detections Using Provenance Graph Structural Features—0
Collective Intelligence: Decentralized Learning for Android Malware Detection in IoT with Blockchain—0
IoT Malware Detection Architecture using a Novel Channel Boosted and Squeezed CNN—0
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