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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 51–75 of 431 papers

TitleStatusHype
An Efficient Approach For Malware Detection Using PE Header SpecificationCode0
How to Train your Antivirus: RL-based Hardening through the Problem-SpaceCode0
Improving Robustness of ML Classifiers against Realizable Evasion Attacks Using Conserved FeaturesCode0
Imbalanced malware classification: an approach based on dynamic classifier selectionCode0
Generating Adversarial Malware Examples for Black-Box Attacks Based on GANCode0
Evaluating the Robustness of Adversarial Defenses in Malware Detection SystemsCode0
Evading Malware Classifiers via Monte Carlo Mutant Feature DiscoveryCode0
Fast & Furious: Modelling Malware Detection as Evolving Data StreamsCode0
How to 0wn NAS in Your Spare TimeCode0
Improving Adversarial Robustness in Android Malware Detection by Reducing the Impact of Spurious CorrelationsCode0
MaMaDroid2.0 -- The Holes of Control Flow GraphsCode0
Efficient Formal Safety Analysis of Neural NetworksCode0
Efficient Concept Drift Handling for Batch Android Malware Detection ModelsCode0
Evaluating Explanation Methods for Deep Learning in SecurityCode0
Dynamic Malware Analysis with Feature Engineering and Feature LearningCode0
Detecting DGA domains with recurrent neural networks and side informationCode0
DetectBERT: Towards Full App-Level Representation Learning to Detect Android MalwareCode0
Deep Transfer Learning for Static Malware ClassificationCode0
Accelerating Malware Classification: A Vision Transformer SolutionCode0
DeepXplore: Automated Whitebox Testing of Deep Learning SystemsCode0
Level Up with ML Vulnerability Identification: Leveraging Domain Constraints in Feature Space for Robust Android Malware DetectionCode0
Deep learning at the shallow end: Malware classification for non-domain expertsCode0
Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust Deep LearningCode0
Cyber Security Data Science: Machine Learning Methods and their Performance on Imbalanced DatasetsCode0
Adversarially Robust Learning with Optimal Transport Regularized DivergencesCode0
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