Attacks and Intrusion Detection in Cloud Computing Using Neural Networks and Particle Swarm Optimization Algorithms

Attacks and Intrusion Detection in Cloud Computing Using Neural Networks and Particle Swarm Optimization Algorithms

Today, cloud computing has become popular among users in organizations and companies. Security and efficiency are the two major issues facing cloud service providers and their customers. Since cloud computing is a virtual pool of resources provided in an open environment (Internet), cloud-based serv...

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Bibliographic Details
Main Authors: Ahmad Shokuh Saljoughi, Mehrdad Mehrvarz, Hamid Mirvaziri
Format: Article
Language:English
Published: Ital Publication 2017-12-01
Series:Emerging Science Journal
Subjects:
Cloud Security
Intrusion Detection
Neural Networks
Particle Swarm Optimization.
Online Access:https://ijournalse.org/index.php/ESJ/article/view/30
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spelling doaj-7ba5aef1a23d41ba9c51e766fec95af62020-11-25T01:27:31ZengItal PublicationEmerging Science Journal2610-91822017-12-011417919110.28991/ijse-0112020Attacks and Intrusion Detection in Cloud Computing Using Neural Networks and Particle Swarm Optimization AlgorithmsAhmad Shokuh Saljoughi0Mehrdad Mehrvarz1Hamid Mirvaziri2Student, Department of Computer Engineering, Shahid Bahonar University, kerman, IranStudent, Department of Computer Engineering, University of Science and Technology, Tehran, IranAssiatant Professor,Department of Electrical and Computer Engineering, Shahid Bahonar University, Kerman, IranToday, cloud computing has become popular among users in organizations and companies. Security and efficiency are the two major issues facing cloud service providers and their customers. Since cloud computing is a virtual pool of resources provided in an open environment (Internet), cloud-based services entail security risks. Detection of intrusions and attacks through unauthorized users is one of the biggest challenges for both cloud service providers and cloud users. In the present study, artificial intelligence techniques, e.g. MLP Neural Network sand particle swarm optimization algorithm, were used to detect intrusion and attacks. The methods were tested for NSL-KDD, KDD-CUP datasets. The results showed improved accuracy in detecting attacks and intrusions by unauthorized users.https://ijournalse.org/index.php/ESJ/article/view/30Cloud SecurityIntrusion DetectionNeural NetworksParticle Swarm Optimization.
collection DOAJ
language English
format Article
sources DOAJ
author Ahmad Shokuh Saljoughi
Mehrdad Mehrvarz
Hamid Mirvaziri
spellingShingle Ahmad Shokuh Saljoughi
Mehrdad Mehrvarz
Hamid Mirvaziri
Attacks and Intrusion Detection in Cloud Computing Using Neural Networks and Particle Swarm Optimization Algorithms
Emerging Science Journal
Cloud Security
Intrusion Detection
Neural Networks
Particle Swarm Optimization.
author_facet Ahmad Shokuh Saljoughi
Mehrdad Mehrvarz
Hamid Mirvaziri
author_sort Ahmad Shokuh Saljoughi
title Attacks and Intrusion Detection in Cloud Computing Using Neural Networks and Particle Swarm Optimization Algorithms
title_short Attacks and Intrusion Detection in Cloud Computing Using Neural Networks and Particle Swarm Optimization Algorithms
title_full Attacks and Intrusion Detection in Cloud Computing Using Neural Networks and Particle Swarm Optimization Algorithms
title_fullStr Attacks and Intrusion Detection in Cloud Computing Using Neural Networks and Particle Swarm Optimization Algorithms
title_full_unstemmed Attacks and Intrusion Detection in Cloud Computing Using Neural Networks and Particle Swarm Optimization Algorithms
title_sort attacks and intrusion detection in cloud computing using neural networks and particle swarm optimization algorithms
publisher Ital Publication
series Emerging Science Journal
issn 2610-9182
publishDate 2017-12-01
description Today, cloud computing has become popular among users in organizations and companies. Security and efficiency are the two major issues facing cloud service providers and their customers. Since cloud computing is a virtual pool of resources provided in an open environment (Internet), cloud-based services entail security risks. Detection of intrusions and attacks through unauthorized users is one of the biggest challenges for both cloud service providers and cloud users. In the present study, artificial intelligence techniques, e.g. MLP Neural Network sand particle swarm optimization algorithm, were used to detect intrusion and attacks. The methods were tested for NSL-KDD, KDD-CUP datasets. The results showed improved accuracy in detecting attacks and intrusions by unauthorized users.
topic Cloud Security
Intrusion Detection
Neural Networks
Particle Swarm Optimization.
url https://ijournalse.org/index.php/ESJ/article/view/30
work_keys_str_mv AT ahmadshokuhsaljoughi attacksandintrusiondetectionincloudcomputingusingneuralnetworksandparticleswarmoptimizationalgorithms
AT mehrdadmehrvarz attacksandintrusiondetectionincloudcomputingusingneuralnetworksandparticleswarmoptimizationalgorithms
AT hamidmirvaziri attacksandintrusiondetectionincloudcomputingusingneuralnetworksandparticleswarmoptimizationalgorithms
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