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

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Showing 376–400 of 431 papers

TitleStatusHype
Is feature selection secure against training data poisoning?—0
Semantic Adversarial Deep Learning—0
Clipping free attacks against artificial neural networks—0
Recurrent Neural Network Attention Mechanisms for Interpretable System Log Anomaly Detection—0
Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust Deep LearningCode0
Explaining Black-box Android Malware Detection—0
An investigation of the classifiers to detect android malicious apps—0
WebEye - Automated Collection of Malicious HTTP Traffic—0
NtMalDetect: A Machine Learning Approach to Malware Detection Using Native API System Calls—0
Deceiving End-to-End Deep Learning Malware Detectors using Adversarial Examples—0
Arhuaco: Deep Learning and Isolation Based Security for Distributed High-Throughput ComputingCode0
HeNet: A Deep Learning Approach on Intel^ Processor Trace for Effective Exploit Detection—0
Clipping Free Attacks Against Neural Networks—0
Android Malware Detection using Deep Learning on API Method Sequences—0
Improving Malware Detection Accuracy by Extracting Icon InformationCode0
Learning Fast and Slow: PROPEDEUTICA for Real-time Malware Detection—0
DeepSign: Deep Learning for Automatic Malware Signature Generation and ClassificationCode0
Enhanced Attacks on Defensively Distilled Deep Neural Networks—0
Decentralised firewall for malware detection—0
Convolutional Neural Network for Classification of Malware Assembly CodeCode0
Malware Detection by Eating a Whole EXECode1
Learning the PE Header, Malware Detection with Minimal Domain KnowledgeCode1
On Security and Sparsity of Linear Classifiers for Adversarial Settings—0
Towards Poisoning of Deep Learning Algorithms with Back-gradient Optimization—0
Improving Robustness of ML Classifiers against Realizable Evasion Attacks Using Conserved FeaturesCode0
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