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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 351–400 of 431 papers

TitleStatusHype
Adversarial Samples on Android Malware Detection Systems for IoT Systems—0
Machine Learning With Feature Selection Using Principal Component Analysis for Malware Detection: A Case Study—0
A Combination Method for Android Malware Detection Based on Control Flow Graphs and Machine Learning Algorithms—0
Android Malware Detection Using Machine Learning on Image Patterns—0
Transfer Learning for Image-Based Malware ClassificationCode0
Using Deep Neural Network for Android Malware Detection—0
Android Malware Detection Using Autoencoder—0
Malware Detection Using Dynamic Birthmarks—0
A Review on The Use of Deep Learning in Android Malware Detection—0
Deep Transfer Learning for Static Malware ClassificationCode0
A short review on Applications of Deep learning for Cyber security—0
Behavioral Malware Classification using Convolutional Recurrent Neural Networks—0
AiDroid: When Heterogeneous Information Network Marries Deep Neural Network for Real-time Android Malware Detection—0
Exploring Adversarial Examples in Malware Detection—0
Detecting DGA domains with recurrent neural networks and side informationCode0
An End-to-End Deep Learning Architecture for Classification of Malware’s Binary Content—0
Statistical Estimation of Malware Detection Metrics in the Absence of Ground TruthCode0
Efficient Formal Safety Analysis of Neural NetworksCode0
HashTran-DNN: A Framework for Enhancing Robustness of Deep Neural Networks against Adversarial Malware Samples—0
Comparison of Deep Learning and the Classical Machine Learning Algorithm for the Malware Detection—0
An investigation of a deep learning based malware detection system—0
apk2vec: Semi-supervised multi-view representation learning for profiling Android applications—0
Using Randomness to Improve Robustness of Machine-Learning Models Against Evasion Attacks—0
Deep learning at the shallow end: Malware classification for non-domain expertsCode0
Robust Neural Malware Detection Models for Emulation Sequence LearningCode0
Static Malware Detection & Subterfuge: Quantifying the Robustness of Machine Learning and Current Anti-Virus—0
SemEval-2018 Task 8: Semantic Extraction from CybersecUrity REports using Natural Language Processing (SecureNLP)—0
On the Effectiveness of System API-Related Information for Android Ransomware Detection—0
Is feature selection secure against training data poisoning?—0
Semantic Adversarial Deep Learning—0
Clipping free attacks against artificial neural networks—0
Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust Deep LearningCode0
Recurrent Neural Network Attention Mechanisms for Interpretable System Log Anomaly Detection—0
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
On Security and Sparsity of Linear Classifiers for Adversarial Settings—0
Towards Poisoning of Deep Learning Algorithms with Back-gradient Optimization—0
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