2016
DOI: 10.11591/ijece.v6i5.pp2432-2436
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Review of IDS Develepment Methods in Machine Learning

Abstract: <p>Due to the rapid advancement of knowledge and technologies, the problem of decision making is getting more sophisticated to address, therefore the inventing of new methods to solve it is very important. One of the promising directions in machine learning and data mining is classifier combination. The popularity of this approach is confirmed by the still growing number of publications. This review paper focuses mainly on classifier combination known also as combined classifier, multiple classifier syst… Show more

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Cited by 9 publications
(7 citation statements)
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“…Older strategies, such as firewalls and antivirus software, are unable to offer solutions to complex cyberattacks [10]. Machine learning and deep learning algorithms are now used to detect intrusion in networks [12][13][14]. Algorithms can also be developed to perform both in group strategies and in combination.…”
Section: Introductionmentioning
confidence: 99%
“…Older strategies, such as firewalls and antivirus software, are unable to offer solutions to complex cyberattacks [10]. Machine learning and deep learning algorithms are now used to detect intrusion in networks [12][13][14]. Algorithms can also be developed to perform both in group strategies and in combination.…”
Section: Introductionmentioning
confidence: 99%
“…Algorithms used for classification can be utilized to make decisions while detecting intrusions in networks [11]. Various machine learning algorithms such as decision trees, K nearest neighbor (KNN), support vector machine (SVM), Naive Bayes, neural networks, random forest, and fuzzy logic are being used for intrusion detection [12][13][14].…”
Section: Introductionmentioning
confidence: 99%
“…r j = r 0 j 1 − e' (−γ * ) An artificial neuron comprises interconnected processing units responsible for processing in parallel and assigns inputs to the required outputs. The output gained from the artificial neuron is illustrated as Equation (12). The DNN model consists of the following layers: output layer, hidden layers, and input layer.…”
mentioning
confidence: 99%
“…Network intrusion detection is a major decision-making problem that can be addressed by the application of classification algorithms [3]. Several machine learning algorithms like fuzzy logic, neural networks, support vector machine, Naïve Bayes, K nearest neighbor, and decision trees have been employed in the field of network intrusion detection [4]. Whenever a combination or an ensemble approach is introduced, performance of individual algorithms can be enhanced.…”
Section: Introductionmentioning
confidence: 99%