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
Mind Your Weight(s): A Large-scale Study on Insufficient Machine Learning Model Protection in Mobile AppsCode1
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
Practical Fast Gradient Sign Attack against Mammographic Image Classifier—0
Interpreting Machine Learning Malware Detectors Which Leverage N-gram AnalysisCode0
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 Threat of Adversarial Attacks on Machine Learning in Network Security -- A Survey—0
The Naked Sun: Malicious Cooperation Between Benign-Looking Processes—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
A Hierarchical Convolutional Neural Network for Malware Classification—0
COPYCAT: Practical Adversarial Attacks on Visualization-Based Malware Detection—0
I-MAD: Interpretable Malware Detector Using Galaxy Transformer—0
Effectiveness of Adversarial Examples and Defenses for Malware Classification—0
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