Machine and deep learning classifiers for binary and multi-class network intrusion detection systems Article Swipe

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Ahmad ALoqaily , Emad Eddien Abdallah , Esraa Abu Elsoud , Yazan Hamdan , Khaled Jallad , Ahmad ALoqaily , Emad Eddien Abdallah , Esraa Abu Elsoud , Yazan Hamdan , Khaled Jallad ·

YOU? · · 2025 · Open Access · · DOI: https://doi.org/10.11591/ijai.v14.i6.pp4814-4827

The rapid proliferation of the internet and advancements in communication technologies have significantly improved networking and increased data vol ume. This phenomenon has subsequently caused a multitude of novel attacks, thereby presenting significant challenges for network security in the intrusion detection system (IDS). Moreover, the ongoing threat from authorized entities who try to carry out various types of attacks on the network is a concern that must be handled seriously. IDS are used to provide network availability, confidentiality, and integrity by employing machine learning (ML) and deep learning (DL) algorithms. This research aimed to study the impacts of the binary and multi-attack instances label by establishing IDS that leverages hybrid algorithms, including artificial neural networks (ANN), random forest (RF), and logistic model trees (LMTs). The paper addresses challenges such as data pre processing, feature selection, and managing imbalanced datasets by applying synthetic minority oversampling technique (SMOTE) and Pearson’s correlation methodologies. The IDS was tested using network security laboratory knowledge discovery datasets (NSL-KDD) and catalonia independence corpus intrusion detection system (CIC-IDS-2017) datasets, achieving an average F1-score of 96% for binary classification on NSL-KDD and 85% for binary classification on CIC-IDS-2017, while for multi-classification, the proposed model achieved an average F1-score of 82% and 96% for NSL-KDD and CIC-IDS-2017 successively.

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Computer science Artificial intelligence Intrusion detection system Deep learning Machine learning Random forest Artificial neural network Feature (linguistics) Binary classification Data mining Network security Binary number Oversampling The Internet Deep belief network Binary data Information security Big data Feature extraction Supervised learning Binary Independence Model Deep neural networks

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Landing Page: https://doi.org/10.11591/ijai.v14.i6.pp4814-4827
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DOI: https://doi.org/10.11591/ijai.v14.i6.pp4814-4827

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Title: Machine and deep learning classifiers for binary and multi-class network intrusion detection systems

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Publication year: 2025

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Publication date: 2025-12-01

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Authors: Ahmad ALoqaily, Emad Eddien Abdallah, Esraa Abu Elsoud, Yazan Hamdan, Khaled Jallad, Ahmad ALoqaily, Emad Eddien Abdallah, Esraa Abu Elsoud, Yazan Hamdan, Khaled Jallad

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Landing page: https://doi.org/10.11591/ijai.v14.i6.pp4814-4827

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Concepts: Computer science, Artificial intelligence, Intrusion detection system, Deep learning, Machine learning, Random forest, Artificial neural network, Feature (linguistics), Binary classification, Data mining, Network security, Binary number, Oversampling, The Internet, Deep belief network, Binary data, Information security, Big data, Feature extraction, Supervised learning, Binary Independence Model, Deep neural networks

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abstract_inverted_index.is	62
abstract_inverted_index.of	3, 27, 57, 97, 175, 199
abstract_inverted_index.on	59, 180, 187
abstract_inverted_index.to	52, 73, 93
abstract_inverted_index.82%	200
abstract_inverted_index.85%	183
abstract_inverted_index.96%	176, 202
abstract_inverted_index.IDS	70, 106, 151
abstract_inverted_index.The	0, 124, 150
abstract_inverted_index.and	6, 15, 78, 85, 100, 119, 135, 146, 162, 182, 201, 205
abstract_inverted_index.are	71
abstract_inverted_index.for	34, 177, 184, 190, 203
abstract_inverted_index.has	22
abstract_inverted_index.out	54
abstract_inverted_index.pre	131
abstract_inverted_index.the	4, 38, 44, 60, 95, 98, 192
abstract_inverted_index.try	51
abstract_inverted_index.vol	18
abstract_inverted_index.was	152
abstract_inverted_index.who	50
abstract_inverted_index.(DL)	88
abstract_inverted_index.(ML)	84
abstract_inverted_index.This	20, 90
abstract_inverted_index.data	17, 130
abstract_inverted_index.deep	86
abstract_inverted_index.from	47
abstract_inverted_index.have	11
abstract_inverted_index.must	66
abstract_inverted_index.such	128
abstract_inverted_index.that	65, 107
abstract_inverted_index.ume.	19
abstract_inverted_index.used	72
abstract_inverted_index.(RF),	118
abstract_inverted_index.aimed	92
abstract_inverted_index.carry	53
abstract_inverted_index.label	103
abstract_inverted_index.model	121, 194
abstract_inverted_index.novel	28
abstract_inverted_index.paper	125
abstract_inverted_index.rapid	1
abstract_inverted_index.study	94
abstract_inverted_index.trees	122
abstract_inverted_index.types	56
abstract_inverted_index.using	154
abstract_inverted_index.while	189
abstract_inverted_index.(ANN),	115
abstract_inverted_index.(IDS).	42
abstract_inverted_index.binary	99, 178, 185
abstract_inverted_index.caused	24
abstract_inverted_index.corpus	165
abstract_inverted_index.forest	117
abstract_inverted_index.hybrid	109
abstract_inverted_index.neural	113
abstract_inverted_index.random	116
abstract_inverted_index.system	41, 168
abstract_inverted_index.tested	153
abstract_inverted_index.threat	46
abstract_inverted_index.(LMTs).	123
abstract_inverted_index.(SMOTE)	145
abstract_inverted_index.NSL-KDD	181, 204
abstract_inverted_index.attacks	58
abstract_inverted_index.average	173, 197
abstract_inverted_index.concern	64
abstract_inverted_index.feature	133
abstract_inverted_index.handled	68
abstract_inverted_index.impacts	96
abstract_inverted_index.machine	82
abstract_inverted_index.network	35, 61, 75, 155
abstract_inverted_index.ongoing	45
abstract_inverted_index.provide	74
abstract_inverted_index.thereby	30
abstract_inverted_index.various	55
abstract_inverted_index.F1-score	174, 198
abstract_inverted_index.achieved	195
abstract_inverted_index.applying	140
abstract_inverted_index.attacks,	29
abstract_inverted_index.datasets	138, 160
abstract_inverted_index.entities	49
abstract_inverted_index.improved	13
abstract_inverted_index.internet	5
abstract_inverted_index.learning	83, 87
abstract_inverted_index.logistic	120
abstract_inverted_index.managing	136
abstract_inverted_index.minority	142
abstract_inverted_index.networks	114
abstract_inverted_index.proposed	193
abstract_inverted_index.research	91
abstract_inverted_index.security	36, 156
abstract_inverted_index.(NSL-KDD)	161
abstract_inverted_index.Moreover,	43
abstract_inverted_index.achieving	171
abstract_inverted_index.addresses	126
abstract_inverted_index.catalonia	163
abstract_inverted_index.datasets,	170
abstract_inverted_index.detection	40, 167
abstract_inverted_index.discovery	159
abstract_inverted_index.employing	81
abstract_inverted_index.including	111
abstract_inverted_index.increased	16
abstract_inverted_index.instances	102
abstract_inverted_index.integrity	79
abstract_inverted_index.intrusion	39, 166
abstract_inverted_index.knowledge	158
abstract_inverted_index.leverages	108
abstract_inverted_index.multitude	26
abstract_inverted_index.synthetic	141
abstract_inverted_index.technique	144
abstract_inverted_index.artificial	112
abstract_inverted_index.authorized	48
abstract_inverted_index.challenges	33, 127
abstract_inverted_index.imbalanced	137
abstract_inverted_index.laboratory	157
abstract_inverted_index.networking	14
abstract_inverted_index.phenomenon	21
abstract_inverted_index.presenting	31
abstract_inverted_index.selection,	134
abstract_inverted_index.seriously.	69
abstract_inverted_index.Pearson’s	147
abstract_inverted_index.algorithms,	110
abstract_inverted_index.algorithms.	89
abstract_inverted_index.correlation	148
abstract_inverted_index.processing,	132
abstract_inverted_index.significant	32
abstract_inverted_index.CIC-IDS-2017	206
abstract_inverted_index.advancements	7
abstract_inverted_index.establishing	105
abstract_inverted_index.independence	164
abstract_inverted_index.multi-attack	101
abstract_inverted_index.oversampling	143
abstract_inverted_index.subsequently	23
abstract_inverted_index.technologies	10
abstract_inverted_index.CIC-IDS-2017,	188
abstract_inverted_index.availability,	76
abstract_inverted_index.communication	9
abstract_inverted_index.proliferation	2
abstract_inverted_index.significantly	12
abstract_inverted_index.successively.	207
abstract_inverted_index.(CIC-IDS-2017)	169
abstract_inverted_index.classification	179, 186
abstract_inverted_index.methodologies.	149
abstract_inverted_index.confidentiality,	77
abstract_inverted_index.multi-classification,	191
cited_by_percentile_year
countries_distinct_count	1
institutions_distinct_count	10
citation_normalized_percentile.value	0.83368161
citation_normalized_percentile.is_in_top_1_percent	False
citation_normalized_percentile.is_in_top_10_percent	True