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General-purpose Unsupervised Cyber Anomaly Detection via Non-negative Tensor Factorization

https://doi.org/10.1145/3519602

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Nonnegative approximations of nonnegative tensors

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The Expression of a Tensor or a Polyadic as a Sum of Products

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Anomaly Detection Using Nonnegative Matrix Factorization

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Anomaly Detection with Score Functions Based on the Reconstruction Error of the Kernel PCA

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Some Mathematical Notes on Three-Mode Factor Analysis

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Distributed non-negative matrix factorization with determination of the number of latent features

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UGR‘16: A new dataset for the evaluation of cyclostationarity-based network IDSs

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L-SVM: A radius-margin-based SVM algorithm with LogDet regularization

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Advances in neural information processing systems 7

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Verizon: Data Breach Investigations Report 2020

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Learning the parts of objects by non-negative matrix factorization

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The harmonic mean p -value for combining dependent tests

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Newton-based optimization for Kullback–Leibler nonnegative tensor factorizations

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Determination of latent dimensionality in international trade flow

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Introducing DeepBalance: Random deep belief network ensembles to address class imbalance

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GEE: A Gradient-based Explainable Variational Autoencoder for Network Anomaly Detection

inferredcites →https://doi.org/10.1109/cybersec.2016.017openalex-snapshot

Cyber Security through Multidimensional Data Decompositions

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Time of Day Anomaly Detection

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TENSOR ENSEMBLE LEARNING FOR MULTIDIMENSIONAL DATA

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Network Intrusion Detection Using Clustering and Gradient Boosting

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HiCS: High Contrast Subspaces for Density-Based Outlier Ranking

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Adversarially Learned Anomaly Detection

inferredcites →https://doi.org/10.1109/icmla51294.2020.00060openalex-snapshot

Semantic Nonnegative Matrix Factorization with Automatic Model Determination for Topic Modeling

inferredcites →https://doi.org/10.1109/icsitech46713.2019.8987531openalex-snapshot

Anomaly-based Intrusion Detection and Prevention Using Adaptive Boosting in Software-defined Network

inferredcites →https://doi.org/10.1109/isi.2016.7745472openalex-snapshot

Poisson factorization for peer-based anomaly detection

inferredcites →https://doi.org/10.1109/isi49825.2020.9280524openalex-snapshot

Multi-Dimensional Anomalous Entity Detection via Poisson Tensor Factorization

inferredcites →https://doi.org/10.1109/tifs.2019.2894358openalex-snapshot

Semi-Supervised Multivariate Statistical Network Monitoring for Learning Security Threats

inferredcites →https://doi.org/10.1109/tpami.2015.2392756openalex-snapshot

Bayesian CP Factorization of Incomplete Tensors with Automatic Rank Determination

inferredcites →https://doi.org/10.1137/07070111xopenalex-snapshot

Tensor Decompositions and Applications

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Outlier Detection with Autoencoder Ensembles

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On Tensors, Sparsity, and Nonnegative Factorizations

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Semialgebraic Geometry of Nonnegative Tensor Rank

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Unified Host and Network Data Set

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Classification of Red Team Authentication Events in an Enterprise Network

inferredcites →https://doi.org/10.1145/1081870.1081891openalex-snapshot

Feature bagging for outlier detection

inferredcites →https://doi.org/10.1145/1571941.1572114openalex-snapshot

Reciprocal rank fusion outperforms condorcet and individual rank learning methods

inferredcites →https://doi.org/10.1145/1921632.1921636openalex-snapshot

Temporal Link Prediction Using Matrix and Tensor Factorizations

inferredcites →https://doi.org/10.1145/2133360.2133363openalex-snapshot

Isolation-Based Anomaly Detection

inferredcites →https://doi.org/10.1145/2783258.2783414openalex-snapshot

Bayesian Poisson Tensor Factorization for Inferring Multilateral Relations from Sparse Dyadic Event Counts

inferredcites →https://doi.org/10.1145/3297280.3297415openalex-snapshot

Real-time botnet detection using nonnegative tucker decomposition

inferredcites →https://doi.org/10.1145/3439950openalex-snapshot

Deep Learning for Anomaly Detection

inferredcites →https://doi.org/10.1214/21-aoas1540openalex-snapshot

Graph link prediction in computer networks using Poisson matrix factorisation

inferredcites →https://doi.org/10.3390/app10051775openalex-snapshot

Towards a Reliable Comparison and Evaluation of Network Intrusion Detection Systems Based on Machine Learning Approaches

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A Local Feature Engineering Strategy to Improve Network Anomaly Detection

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Scikit-learn: Machine Learning in Python

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A Probabilistic-driven Ensemble Approach to Perform Event Classification in Intrusion Detection System

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Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Classification of Malware Families Under Extreme Class Imbalance Using Non-Negative Tensor Decomposition

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A Comparative Study of Rule-Based and Machine Learning-Based Methods for Authentication Anomaly Detection

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A Holistic review and performance evaluation of unsupervised learning methods for network anomaly detection

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Unsupervised Anomaly Detection and Explanation in Network Traffic with Transformers

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