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A classification model based on svm and fuzzy rough set for network intrusion detection

https://doi.org/10.3233/jifs-191621

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What this work says

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

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Dependability‐based cluster weighting in clustering ensemble

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Introducing a Classification Model Based on SVM for Network Intrusion Detection

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Distance-Based Classification with Lipschitz Functions

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Opcode-Sequence-Based Semi-supervised Unknown Malware Detection

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Support-Vector Networks

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Rough sets

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A novel SVM by combining kernel principal component analysis and improved chaotic particle swarm optimization for intrusion detection

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Fuzzy rough sets: Application to feature selection

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A hybrid network intrusion detection framework based on random forests and weighted k-means

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A novel hybrid KPCA and SVM with GA model for intrusion detection

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Evolving statistical rulesets for network intrusion detection

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A novel SVM-kNN-PSO ensemble method for intrusion detection system

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Rough set feature selection and rule induction for prediction of malignancy degree in brain glioma

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Deep feature learnt by conventional deep neural network

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Feature deduction and ensemble design of intrusion detection systems

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Fuzzy-rough imbalanced learning for the diagnosis of High Voltage Circuit Breaker maintenance: The SMOTE-FRST-2T algorithm

inferredcites →https://doi.org/10.1016/j.eswa.2015.07.015openalex-snapshot

An intrusion detection system using network traffic profiling and online sequential extreme learning machine

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Reliability-based fuzzy clustering ensemble

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A survey of multiple classifier systems as hybrid systems

inferredcites →https://doi.org/10.1016/j.ins.2006.06.006openalex-snapshot

Rough sets: Some extensions

inferredcites →https://doi.org/10.1016/j.ins.2006.06.007openalex-snapshot

Rough sets and Boolean reasoning

inferredcites →https://doi.org/10.1016/j.neucom.2016.04.015openalex-snapshot

Missing data imputation using fuzzy-rough methods

inferredcites →https://doi.org/10.1016/j.neucom.2017.06.082openalex-snapshot

Using sub-sampling and ensemble clustering techniques to improve performance of imbalanced classification

inferredcites →https://doi.org/10.1016/j.patcog.2016.02.013openalex-snapshot

Feature selection in mixed data: A method using a novel fuzzy rough set-based information entropy

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Minimal approximate hitting sets and rule templates

inferredcites →https://doi.org/10.1016/s1389-1286(00)00139-0openalex-snapshot

The 1999 DARPA off-line intrusion detection evaluation

inferredcites →https://doi.org/10.1080/02664763.2017.1363163openalex-snapshot

Diverse classifier ensemble creation based on heuristic dataset modification

inferredcites →https://doi.org/10.1089/end.2016.0791openalex-snapshot

Artificial Neural Network System to Predict the Postoperative Outcome of Percutaneous Nephrolithotomy

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Identifying and Benchmarking Key Features for Cyber Intrusion Detection: An Ensemble Approach

inferredcites →https://doi.org/10.1109/aciids.2009.59openalex-snapshot

Using Rough Set and Support Vector Machine for Network Intrusion Detection System

inferredcites →https://doi.org/10.1109/cec.2013.6557670openalex-snapshot

MapReduce intrusion detection system based on a particle swarm optimization clustering algorithm

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/fuzz-ieee.2019.8858799openalex-snapshot

Effective instance selection using the fuzzy-rough lower approximation

inferredcites →https://doi.org/10.1109/fuzzy.2007.4295518openalex-snapshot

Distance Measure Assisted Rough Set Feature Selection

inferredcites →https://doi.org/10.1109/iccci.2013.6466310openalex-snapshot

Intrusion detection technique by using k-means, fuzzy neural network and SVM classifiers

inferredcites →https://doi.org/10.1109/iccke.2014.6993345openalex-snapshot

A novel framework, based on fuzzy ensemble of classifiers for intrusion detection systems

inferredcites →https://doi.org/10.1109/iccubea.2015.61openalex-snapshot

Intrusion Detection System Using Bagging Ensemble Method of Machine Learning

inferredcites →https://doi.org/10.1109/icetech.2015.7275015openalex-snapshot

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inferredcites →https://doi.org/10.1109/igarss.2005.1526526openalex-snapshot

Hierarchical classification of hyperspectral images by using SVMs and "same class neighborhood property"

inferredcites →https://doi.org/10.1109/surv.2012.121912.00006openalex-snapshot

On the Vital Areas of Intrusion Detection Systems in Wireless Sensor Networks

inferredcites →https://doi.org/10.1109/surv.2013.050113.00191openalex-snapshot

A Survey of Intrusion Detection Systems in Wireless Sensor Networks

inferredcites →https://doi.org/10.1109/surv.2013.052213.00046openalex-snapshot

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Command Filter-Based Adaptive NN Control for MIMO Nonlinear Systems With Full-State Constraints and Actuator Hysteresis

inferredcites →https://doi.org/10.1109/tfuzz.2018.2883374openalex-snapshot

Adaptive Fuzzy Control for Nontriangular Structural Stochastic Switched Nonlinear Systems With Full State Constraints

inferredcites →https://doi.org/10.1109/tfuzz.2019.2895560openalex-snapshot

Observer-Based Fuzzy Adaptive Event-Triggered Control for Pure-Feedback Nonlinear Systems With Prescribed Performance

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Building a Scalable System for Stealthy P2P-Botnet Detection

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A Distance Measure Approach to Exploring the Rough Set Boundary Region for Attribute Reduction

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Gene Regulatory Elements Extraction in Breast Cancer by Hi-C Data Using a Meta-Heuristic Method

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Consensus Function Based on Clusters Clustering and Iterative Fusion of Base Clusters

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CMCABC: Clustering and Memory-Based Chaotic Artificial Bee Colony Dynamic Optimization Algorithm

inferredcites →https://doi.org/10.1166/jmihi.2017.1788openalex-snapshot

Parkinson Detection: An Image Processing Approach

inferredcites →https://doi.org/10.1504/ijbic.2018.094616openalex-snapshot

Optimisation inspiring from behaviour of raining in nature: droplet optimisation algorithm

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Optimisation inspiring from behaviour of raining in nature: droplet optimisation algorithm

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A clustering ensemble learning method based on the ant colony clustering algorithm

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A clustering ensemble learning method based on the ant colony clustering algorithm

inferredcites →https://doi.org/10.1631/jzus.2004.1076openalex-snapshot

Intrusion detection using rough set classification

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An optimization algorithm based on behavior of see-see partridge chicks

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User and item profile expansion for dealing with cold start problem

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An Ensemble of Locally Reliable Cluster Solutions

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Data Reduction with Rough Sets

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Support Vector Machine Solvers

What points at this work

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

inferred← citeshttps://doi.org/10.2139/ssrn.5048254openalex-extracted

A Review of Various Datasets for Machine Learning Algorithm-Based Intrusion Detection System: Advances and Challenges

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Comparative research on network intrusion detection methods based on machine learning

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Convolutional Neural Network Based Power Information Network Security Situational Awareness Model

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Lightweight network intrusion detection method based on improved federated learning

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Ship HRRP target recognition method based on transformer and convolutional attention network

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Intrusion Detection Classification Based on Random Forest

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An Efficient Classification Model using Fuzzy Rough Set Theory and Random Weight Neural Network

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