CR-IOT based selfish attack detection via RSSI-LSTM

Internet of Things-based technologies rely on cooperating between nodes to increase network capacity. A selfish or malicious node is a node that does not cooperate with other nodes in the network. Selfish nodes raise their interests by using facilities provided by other nodes. Selfish cognitive radi...

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Main Authors: S. Sindhuja, Divya Midhun Chakkaravarthy, Janani Selvam
Format: Article
Language:English
Published: Elsevier 2023-06-01
Series:Measurement: Sensors
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S266591742300065X
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author S. Sindhuja
Divya Midhun Chakkaravarthy
Janani Selvam
author_facet S. Sindhuja
Divya Midhun Chakkaravarthy
Janani Selvam
author_sort S. Sindhuja
collection DOAJ
description Internet of Things-based technologies rely on cooperating between nodes to increase network capacity. A selfish or malicious node is a node that does not cooperate with other nodes in the network. Selfish nodes raise their interests by using facilities provided by other nodes. Selfish cognitive radio attacks significantly degrade the performance of Cognitive Radio networks, which pose a serious security threat and malicious nodes often abuse the network and damage its facilities. To overcome this issue, a novel Cognitive radio on-demand distance vector (CRODV) is proposed. The proposed CRODV technique utilize (Received Signal Strength Indicator) RSSI-based Long Short-Term Memory (LSTM) to detect attacks. This is accomplished by counting the number of active channels to and from the test node in a specific area. If the values don't match, the test node in question is self-centered or introverted. If both values are the same, the test node is normal. Simulations were carried out in MATLAB to test the proposed CRODV. A comparison is made between the suggested framework and existing methods in terms of packet delivery ratio, route dis-connectivity ratio, throughput, detection time, and end-to-end delay. The experimental results demonstrates that the CRODV technique reduce the end-to-end delay by 27.4%, 33.24%, and 40.14% when compared with UKF, HMM, and ALAD techniques.
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spelling doaj.art-ac512dd1eea544ffad265d209c0cf46c2023-06-23T04:44:10ZengElsevierMeasurement: Sensors2665-91742023-06-0127100729CR-IOT based selfish attack detection via RSSI-LSTMS. Sindhuja0Divya Midhun Chakkaravarthy1Janani Selvam2Lincoln University College Malaysia, Kelantan, Malaysia; Corresponding author.Department of Engineering, Lincoln University College Malaysia, Kelantan, MalaysiaDepartment of Engineering, Lincoln University College Malaysia, Kelantan, MalaysiaInternet of Things-based technologies rely on cooperating between nodes to increase network capacity. A selfish or malicious node is a node that does not cooperate with other nodes in the network. Selfish nodes raise their interests by using facilities provided by other nodes. Selfish cognitive radio attacks significantly degrade the performance of Cognitive Radio networks, which pose a serious security threat and malicious nodes often abuse the network and damage its facilities. To overcome this issue, a novel Cognitive radio on-demand distance vector (CRODV) is proposed. The proposed CRODV technique utilize (Received Signal Strength Indicator) RSSI-based Long Short-Term Memory (LSTM) to detect attacks. This is accomplished by counting the number of active channels to and from the test node in a specific area. If the values don't match, the test node in question is self-centered or introverted. If both values are the same, the test node is normal. Simulations were carried out in MATLAB to test the proposed CRODV. A comparison is made between the suggested framework and existing methods in terms of packet delivery ratio, route dis-connectivity ratio, throughput, detection time, and end-to-end delay. The experimental results demonstrates that the CRODV technique reduce the end-to-end delay by 27.4%, 33.24%, and 40.14% when compared with UKF, HMM, and ALAD techniques.http://www.sciencedirect.com/science/article/pii/S266591742300065XInternet of thingsCognitive radioCognitive radio on-demand distance vector (CRODV)Long short-term memory (LSTM)Received signal strength indicator (RSSI)
spellingShingle S. Sindhuja
Divya Midhun Chakkaravarthy
Janani Selvam
CR-IOT based selfish attack detection via RSSI-LSTM
Measurement: Sensors
Internet of things
Cognitive radio
Cognitive radio on-demand distance vector (CRODV)
Long short-term memory (LSTM)
Received signal strength indicator (RSSI)
title CR-IOT based selfish attack detection via RSSI-LSTM
title_full CR-IOT based selfish attack detection via RSSI-LSTM
title_fullStr CR-IOT based selfish attack detection via RSSI-LSTM
title_full_unstemmed CR-IOT based selfish attack detection via RSSI-LSTM
title_short CR-IOT based selfish attack detection via RSSI-LSTM
title_sort cr iot based selfish attack detection via rssi lstm
topic Internet of things
Cognitive radio
Cognitive radio on-demand distance vector (CRODV)
Long short-term memory (LSTM)
Received signal strength indicator (RSSI)
url http://www.sciencedirect.com/science/article/pii/S266591742300065X
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AT divyamidhunchakkaravarthy criotbasedselfishattackdetectionviarssilstm
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