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A Survey on the Applications of Semi-supervised Learning to Cyber-security

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A review of Machine Learning-based zero-day attack detection: Challenges and future directions

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Machine Learning

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A survey on adversarial attacks and defences

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One data preprocessing method in high-speed network intrusion detection

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Semi-Supervised K-Means DDoS Detection Method Using Hybrid Feature Selection Algorithm

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Discriminative Autoencoding Framework for Simple and Efficient Anomaly Detection

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Malware Detection via Extended Label Propagation Through Graph Inference

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Semi-Supervised Malware Clustering Based on the Weight of Bytecode and API

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Avoiding Future Digital Extortion Through Robust Protection Against Ransomware Threats Using Deep Learning Based Adaptive Approaches

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Cyber Intrusion Prevention for Large-Scale Semi-Supervised Deep Learning Based on Local and Non-Local Regularization

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Anomaly-Based Intrusion Detection From Network Flow Features Using Variational Autoencoder

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Understanding Shilling Attacks and Their Detection Traits: A Comprehensive Survey

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Design and Development of AD-CGAN: Conditional Generative Adversarial Networks for Anomaly Detection

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An Integrated Model Based on O-GAN and Density Estimation for Anomaly Detection

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A Survey on Machine Learning Techniques for Cyber Security in the Last Decade

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Network Anomaly Detection Using Memory-Augmented Deep Autoencoder

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Multi-Source Multi-Domain Data Fusion for Cyberattack Detection in Power Systems

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Machine-Generated Text: A Comprehensive Survey of Threat Models and Detection Methods

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SMILER: Towards Practical Online Traffic Classification

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Review of semi-supervised method for Intrusion Detection System

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Detecting Packed Executable File: Supervised or Anomaly Detection Method?

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SPR2EP: A Semi-Supervised Spam Review Detection Framework

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Deep Anomaly Detection with Ensemble-Based Active Learning

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Zero-day Malware Detection using Threshold-free Autoencoding Architecture

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Semi-supervised Learning with Concept Drift Using Particle Dynamics Applied to Network Intrusion Detection Data

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Ransomware: Let's fight back!

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Deep Generative Model for Malware Detection

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A Dendritic Cell Immune System Inspired Approach for Stock Market Manipulation Detection

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Intrusion detection based on the semi-supervised Fuzzy C-Means clustering algorithm

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Semi-Supervised Recursive Autoencoders for Social Review Spam Detection

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Fraud detection in big data using supervised and semi-supervised learning techniques

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vSwitchGuard: Defending OpenFlow Switches Against Saturation Attacks

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A Survey of Data Mining and Machine Learning Methods for Cyber Security Intrusion Detection

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A Novel Distributed Semi-Supervised Approach for Detection of Network Based Attacks

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Self-Learning Semi-Supervised Machine Learning for Network Intrusion Detection

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Integer Data Zero-Watermark Assisted System Calls Abstraction and Normalization for Host Based Anomaly Detection Systems

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Multi-Classification for Malicious URL Based on Improved Semi-Supervised Algorithm

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Semi-Supervised Intrusion Detection Method based on Adversarial Autocoder

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A Semi-supervised Learning Methodology for Malware Categorization using Weighted Word Embeddings

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Semi-supervised network traffic classification using deep generative models

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A Novel Distributed Machine Learning Framework for Semi-Supervised Detection of Botnet Attacks

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Hybrid SQL injection detection system

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JCADS: Semi-supervised clustering algorithm for network anomaly intrusion detection systems

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Detection Of Malicious DNS and Web Servers using Graph-Based Approaches

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An Internet Traffic Classification Method Based on Semi-Supervised Support Vector Machine

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A Reliable Semi-Supervised Intrusion Detection Model: One Year of Network Traffic Anomalies

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Intrusion detection for Softwarized Networks with Semi-supervised Federated Learning

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Ransomware Detection with Semi-Supervised Learning

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Detection of DDoS Attacks using Semi-Supervised based Machine Learning Approaches

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Multilayer Intrusion Detection System Based On Semi-supervised Clustering

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Intrusion Detection in Network Systems Through Hybrid Supervised and Unsupervised Machine Learning Process: A Case Study on the ISCX Dataset

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An End-to-End Framework to Identify Pathogenic Social Media Accounts on Twitter

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Building text classifiers using positive and unlabeled examples

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Semi-supervised Density-Based Clustering

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Spammers Detection from Product Reviews: A Hybrid Model

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Effective intrusion detection system using semi-supervised learning

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A Hybrid Learning from Multi-behavior for Malicious Domain Detection on Enterprise Network

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Data-Driven Anomaly Detection for Power System Generation Control

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Predicting unlabeled traffic for intrusion detection using semi-supervised machine learning

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A New Intrusion Detection Method Based on Improved DBSCAN

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Unsupervised Feature Learning With Distributed Stacked Denoising Sparse Autoencoder for Abnormal Behavior Detection Using Apache Spark

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Intrusion Detection Algorithm Based on Semi-supervised Learning

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Aiding Intrusion Analysis Using Machine Learning

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CausalConvLSTM: Semi-Supervised Log Anomaly Detection Through Sequence Modeling

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Deep Learning for Network Anomalies Detection

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Rethinking Robust and Accurate Application Protocol Identification: A Nonparametric Approach

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A New Network Intrusion Detection based on Semi-supervised Dimensionality Reduction and Tri-LightGBM

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Enhancing Web Page Classification via Local Co-training

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A Weak Coupling of Semi-Supervised Learning with Generative Adversarial Networks for Malware Classification

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Misuse and Anomaly Intrusion Detection System using Ensemble Learning Model

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Research on the semi-supervised fuzzy clustering algorithm with pariwise constraints for intrusion detection

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Semi-supervised learning methods for network intrusion detection

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A Network Malicious Traffic Detection Method Based on Semi-Supervised Deep Learning

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Exploiting N-Gram Location for Intrusion Detection

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A Survey on the Role of Artificial Intelligence, Machine Learning and Deep Learning for Cybersecurity Attack Detection

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An Application Traffic Classification Method Based on Semi-Supervised Clustering

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Introducing a Method for Combining Supervised and Semi-Supervised Methods in Fraud Detection

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Semi-supervised GANs for Fraud Detection

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Semi-Supervised Domain-Adversarial Training for Intrusion Detection against False Data Injection in the Smart Grid

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Exploiting mobile social behaviors for Sybil detection

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Poster Abstract: A Semi-Supervised Approach for Network Intrusion Detection Using Generative Adversarial Networks

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Co-training For Image-Based Malware Classification

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A Semi-supervised Intrusion Detection Algorithm Based on Natural Neighbor

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SILU: Strategy Involving Large-scale Unlabeled Logs for Improving Malware Detector

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An Anomaly Intrusion Detection Algorithm Based on Minimal Diversity Semi-supervised Clustering

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Early Identification of Pathogenic Social Media Accounts

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Applying Semi-supervised Cluster Algorithm for Anomaly Detection

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An intrusion detection algorithm based on multi-label learning

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MSML: A Novel Multilevel Semi-Supervised Machine Learning Framework for Intrusion Detection System

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Semi-Supervised Spatiotemporal Deep Learning for Intrusions Detection in IoT Networks

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Semisupervised Federated-Learning-Based Intrusion Detection Method for Internet of Things

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End-to-End Adversarial Learning for Intrusion Detection in Computer Networks

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Federated-Learning-Empowered Semi-Supervised Active Learning Framework for Intrusion Detection in ZSM

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Preventing Poisoning Attacks On AI Based Threat Intelligence Systems

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Security and Privacy Challenges in the Smart Grid

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Network Anomaly Detection Based on Cooperative Semi-Supervised Support Vector Machine

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Network Intrusion Detection based of Semi-Supervised Ensemble Learning Algorithm for Imbalanced Data

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A Robust PCA Feature Selection To Assist Deep Clustering Autoencoder-Based Network Anomaly Detection

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Enhancing Image-Based Malware Classification Using Semi-Supervised Learning

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Online feature selected semi-supervised decision trees for network intrusion detection

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Intrusion Detection System using Semi-Supervised Learning with Adversarial Auto-encoder

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Online Traffic Classification Based on Co-training Method

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Semi-Supervised False Data Detection Using Gated Recurrent Units and Threshold Scoring Algorithm

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