Search Results - (( a detection system algorithm ) OR ( _ classification system algorithm ))
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An enhancement of classification technique based on rough set theory for intrusion detection system application
Published 2019“…An Intrusion Detection System (IDS) is capable to detect unauthorized intrusions into computer systems and networks by looking for signatures of known attacks or deviations of normal activity. …”
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2
Immune Multiagent System for Network Intrusion Detection using Non-linear Classification Algorithm
Published 2010“…A new non classification algorithm was developed based on the danger theory model of human immune system (HIS).The abstract model of system algorithm is inspired from HIS cell mechanism mainly, the Dendritic cell behavior and T-cell mechanisms. …”
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Evaluation of fall detection classification approaches
Published 2012“…In this paper a waist worn fall detection system has been proposed. …”
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Distributed Online Averaged One Dependence Estimator (DOAODE) Algorithm for Multi-class Classification of Network Anomaly Detection System
Published 2019“…Therefore, this paper aims to develop an effective and efficient network anomaly detection system by using distributed online averaged one dependence estimator (DOAODE) classification algorithm for multi-class network data to overcome these issues. …”
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Distributed Online Averaged One Dependence Estimator (DOAODE) Algorithm for Multi-class Classification of Network Anomaly Detection System
Published 2019“…Therefore, this paper aims to develop an effective and efficient network anomaly detection system by using distributed online averaged one dependence estimator (DOAODE) classification algorithm for multi-class network data to overcome these issues. …”
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6
Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System
Published 2020“…Feature selection and classifier parameter tuning are important factors that affect the performance of any intrusion detection system. In this paper, an improved intrusion detection algorithm for multiclass classification was presented and discussed in detail. …”
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Hybrid weight deep belief network algorithm for anomaly-based intrusion detection system
Published 2022“…Recently, researchers suggested a deep belief network (DBN) algorithm to construct and build a network intrusion detection system (NIDS) for detecting attacks that have not been seen before. …”
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Performances of machine learning algorithms for binary classification of network anomaly detection system
Published 2018“…The aim of this paper to build a network anomaly detection system using machine learning algorithms that are efficient, effective and fast processing. …”
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Classification Algorithms and Feature Selection Techniques for a Hybrid Diabetes Detection System
Published 2021“…The proposed method has three steps: preprocessing, feature selection and classification. Several combinations of Harmony search algorithm, genetic algorithm, and particle swarm optimization algorithm are examined with K-means for feature selection. …”
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Mobile machine vision for railway surveillance system using deep learning algorithm
Published 2021“…Trains have been a popular transportation in our daily life. However, there is no proper surveillance system for obstacle detection at the railway, leading to the happen of unwanted accidents. …”
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Proceedings -
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An enhanced classification framework for intrusions detection system using intelligent exoplanet atmospheric retrieval algorithm
Published 2022“…This causes the classifier to be biased, reduce classification accuracy, and increase false alert. To that end, we proposed a model that significantly improve the accuracy of the intrusion detection system by eliminating false alerts, whether they are false negative or false positive negative alerts. …”
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Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm
Published 2023Subjects:Conference Paper -
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SVM for network anomaly detection using ACO feature subset
Published 2016“…This paper proposes a detection model, ant system with support vector machine, which uses ant system, a variation of ant colony optimization, to filter out the redundant and irrelevant features for support vector machine classification algorithm. …”
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Rao-SVM machine learning algorithm for intrusion detection system
Published 2020“…Most of the intrusion detection systems are developed based on optimization algorithms as a result of the increase in audit data features; optimization algorithms are also considered for IDS due to the decline in the performance of the human-based methods in terms of their training time and classification accuracy. …”
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Text spam messages classification using Artificial Immune System (AIS) algorithms
Published 2024thesis::master thesis -
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An analysis of intrusion detection classification using supervised machine learning algorithms on NSL-KDD dataset / Sarthak Rastogi ... [et al.]
Published 2022“…Anomaly based intrusion detection is a type of intrusion detection system that identifies anomalies. …”
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Anomaly detection in ICS datasets with machine learning algorithms
Published 2021“…An Intrusion Detection System (IDS) provides a front-line defense mechanism for the Industrial Control System (ICS) dedicated to keeping the process operations running continuously for 24 hours in a day and 7 days in a week. …”
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Embedded fuzzy classifier for detection and classification of preseizure state using real EEG data
Published 2014“…Therefore, the work presented here includes embedded hardware system that works with classification algorithm on real EEG signals, in a ubiquitous setting. …”
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Breast cancer disease classification using fuzzy-ID3 algorithm with FUZZYDBD method: automatic fuzzy database definition
Published 2021“…This paper proposed the fuzzy-ID3 (FID3) algorithm, a fuzzy decision tree as the classification method in breast cancer detection. …”
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Embedded Fuzzy Classifier for Detection and Classification of Preseizure state using Real EEG data
Published 2014“…Therefore, the work presented here includes embedded hardware system that works with classification algorithm on real EEG signals, in a ubiquitous setting. …”
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