Role of data normalization in k-means algorithm results

Muhammed, Lamia Abed Noor

doi:10.1063/5.0119267

Cited by 1 publication

(1 citation statement)

References 7 publications

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“…Эффективность функционирования ИНС связана, как правило, с удалением части связей между слоями (называемыми также dropput [24]), регуляризацией и нормировкой весовых коэффициентов на этапе обучения (15) [25], упрощением функций активации на уровне скрытых слоев [26].…”

Section: многозначная классификация с помощью инс с множественным вых...unclassified

Multivalued Classification of Computer Attacks Using Artificial Neural Networks with Multiple Outputs

Shelukhin,

Rakovsky

2023

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Modern computer networks (CN), having a complex and often heterogeneous structure, generate large volumes of multi-dimensional multi-label data. Accounting for information about multi-label experimental data (ED) can improve the efficiency of solving a number of information security problems: from CN profiling to detecting and preventing computer attacks on CN. The aim of the work is to develop a multi-label artificial neural network (ANN) architecture for detecting and classifying computer attacks in multi-label ED, and its comparative analysis with known analogues in terms of binary metrics for assessing the quality of classification. A formalization of ANN in terms of matrix algebra is proposed, which allows taking into account the case of multi-label classification and the new architecture of ANN with multiple output using the proposed formalization. The advantage of the proposed formalization is the conciseness of a number of entries associated with the ANN operating mode and learning mode. Proposed architecture allows solving the problems of detecting and classifying multi-label computer attacks, on average, 5% more efficiently than known analogues. The observed gain is due to taking into account multi-label patterns between class labels at the training stage through the use of a common first layer. The advantages of the proposed ANN architecture are scalability to any number of class labels and fast convergence.

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Section: многозначная классификация с помощью инс с множественным вых...unclassified

Multivalued Classification of Computer Attacks Using Artificial Neural Networks with Multiple Outputs

Shelukhin,

Rakovsky

2023

jour

View full text Add to dashboard Cite

show abstract

Role of data normalization in k-means algorithm results

Cited by 1 publication

References 7 publications

Multivalued Classification of Computer Attacks Using Artificial Neural Networks with Multiple Outputs

Multivalued Classification of Computer Attacks Using Artificial Neural Networks with Multiple Outputs

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