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 301–325 of 431 papers

TitleStatusHype
A Review of Computer Vision Methods in Network Security—0
Do Gradient-based Explanations Tell Anything About Adversarial Robustness to Android Malware?—0
How to 0wn the NAS in Your Spare TimeCode0
pAElla: Edge-AI based Real-Time Malware Detection in Data CentersCode0
AdvMS: A Multi-source Multi-cost Defense Against Adversarial Attacks—0
How to 0wn NAS in Your Spare TimeCode0
Analyzing CNN Based Behavioural Malware Detection Techniques on Cloud IaaS—0
MDEA: Malware Detection with Evolutionary Adversarial Learning—0
GLSearch: Maximum Common Subgraph Detection via Learning to Search—0
Can't Boil This Frog: Robustness of Online-Trained Autoencoder-Based Anomaly Detectors to Adversarial Poisoning Attacks—0
Interpreting Machine Learning Malware Detectors Which Leverage N-gram AnalysisCode0
Practical Fast Gradient Sign Attack against Mammographic Image Classifier—0
Towards Deep Federated Defenses Against Malware in Cloud Ecosystems—0
Malware Makeover: Breaking ML-based Static Analysis by Modifying Executable BytesCode0
Towards a Robust Classifier: An MDL-Based Method for Generating Adversarial Examples—0
Coda: An End-to-End Neural Program Decompiler—0
DL-Droid: Deep learning based android malware detection using real devices—0
Classification with Costly Features in Hierarchical Deep SetsCode0
There is Limited Correlation between Coverage and Robustness for Deep Neural Networks—0
The Naked Sun: Malicious Cooperation Between Benign-Looking Processes—0
The Threat of Adversarial Attacks on Machine Learning in Network Security -- A Survey—0
Malware Classification using Deep Learning based Feature Extraction and Wrapper based Feature Selection TechniqueCode0
Heterogeneous Graph Matching Networks—0
Would a File by Any Other Name Seem as Malicious?—0
An MDL-Based Classifier for Transactional Datasets with Application in Malware Detection—0
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