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Unsupervised Labeling for Supervised Anomaly Detection in Enterprise and Cloud Networks
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/s10844-015-0388-xopenalex-snapshot
Two-tier network anomaly detection model: a machine learning approach
inferredcites →https://doi.org/10.1109/asonam.2012.72openalex-snapshot
Network Anomaly Detection Using Co-clustering
inferredcites →https://doi.org/10.1109/cisda.2009.5356528openalex-snapshot
A detailed analysis of the KDD CUP 99 data set
inferredcites →https://doi.org/10.1109/compsacw.2014.25openalex-snapshot
Bayesian Model Averaging of Bayesian Network Classifiers for Intrusion Detection
inferredcites →https://doi.org/10.1109/cscloud.2016.43openalex-snapshot
A Cluster-Based Intrusion Detection Framework for Monitoring the Traffic of Cloud Environments
inferredcites →https://doi.org/10.1109/surv.2013.052213.00046openalex-snapshot
Network Anomaly Detection: Methods, Systems and Tools
inferredcites →https://doi.org/10.7916/d8mp5904openalex-snapshot
Intrusion detection with unlabeled data using clustering
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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State of the Art Literature Review on Network Anomaly Detection with Deep Learning
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Ranking Pathology Data in the Absence of a Ground Truth
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A Semi-supervised Framework for Anomaly Detection and Data Labeling for Industrial Control Systems
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Multivariate network traffic analysis using clustered patterns
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Online fault detection and diagnostics for self powered neutron detector along with its cable using hybrid techniques of noise analysis and clustering algorithm
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Learning-based dynamic cache management in a cloud
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Network anomaly detection using deep learning techniques
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Advances in Landslide Detection through Google Earth Engine: A Comprehensive Review
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Convolutional neural network for intrusion detection using blockchain technology
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A Review of Intrusion Detection and Blockchain Applications in the Cloud: Approaches, Challenges and Solutions
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TRACK-Plus: Optimizing Artificial Neural Networks for Hybrid Anomaly Detection in Data Streaming Systems
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Machine Learning in Network Anomaly Detection: A Survey
inferred← citeshttps://doi.org/10.1109/cybermatics_2018.2018.00167openalex-snapshot
Hybrid Relabeled Model for Network Intrusion Detection
inferred← citeshttps://doi.org/10.1109/icai58407.2023.10136687openalex-snapshot
A Hybrid Learning Approach for Automatic Data Labelling and Anomaly Detection in IoT Networks
inferred← citeshttps://doi.org/10.1109/icdcs.2018.00178openalex-snapshot
An Empirical Study on Network Anomaly Detection Using Convolutional Neural Networks
inferred← citeshttps://doi.org/10.1109/icmla.2019.00083openalex-snapshot
A Comparative Analysis of Unsupervised Learning Techniques for Anomaly Detection in Railway Systems
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Anomaly Detection in Large-Scale Cloud Systems: An Industry Case and Dataset
inferred← citeshttps://doi.org/10.1109/lcn53696.2022.9843419openalex-snapshot
Accurate Real-Time Labeling of Application Traffic
inferred← citeshttps://doi.org/10.1109/rusautocon.2019.8867696openalex-snapshot
Attack Detection in Enterprise Networks by Machine Learning Methods
inferred← citeshttps://doi.org/10.1109/sera.2019.8886794openalex-snapshot
Hybrid Intrusion Detection System Using Machine Learning Techniques in Cloud Computing Environments
inferred← citeshttps://doi.org/10.1109/sisy62279.2024.10737577openalex-snapshot
Enhancing One-Class Anomaly Detection in Unlabeled Datasets Through Unsupervised Data Refinement
inferred← citeshttps://doi.org/10.1109/tkde.2021.3050400openalex-snapshot
An Online Offline Framework for Anomaly Scoring and Detecting New Traffic in Network Streams
inferred← citeshttps://doi.org/10.1109/tkde.2024.3523857openalex-snapshot
A Survey of Change Point Detection in Dynamic Graphs
inferred← citeshttps://doi.org/10.1109/tnsm.2020.3016246openalex-snapshot
Survey of Network Intrusion Detection Methods From the Perspective of the Knowledge Discovery in Databases Process
inferred← citeshttps://doi.org/10.1109/tnsm.2020.3048131openalex-snapshot
STAD: Spatio-Temporal Anomaly Detection Mechanism for Mobile Network Management
inferred← citeshttps://doi.org/10.1145/3446636openalex-snapshot
Automated Feature Selection for Anomaly Detection in Network Traffic Data
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A Systematic Review of Defensive and Offensive Cybersecurity with Machine Learning
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SDN-Enabled Hybrid DL-Driven Framework for the Detection of Emerging Cyber Threats in IoT
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A Software Deep Packet Inspection System for Network Traffic Analysis and Anomaly Detection
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Live Migration Timing Optimization for VMware Environments using Machine Learning Techniques
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Dynamic network resources optimization based on machine learning and cellular data mining
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