A Trust Model for Detecting Device Attacks in Mobile Ad Hoc Ambient Home Network
International Journal of Advanced Pervasive and Ubiquitous Computing, Vol 2, p.17
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International Journal of Advanced Pervasive and Ubiquitous Computing
2020
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| Liŋkkat: | https://ir.oauife.edu.ng/handle/123456789/5036 |
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| _version_ | 1810764577904787456 |
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| author | Solomon, Akinboro Olajubu, Emmanuel Ogundoyin, Ibrahim Aderounmu, Ganiyu |
| author_facet | Solomon, Akinboro Olajubu, Emmanuel Ogundoyin, Ibrahim Aderounmu, Ganiyu |
| author_sort | Solomon, Akinboro |
| collection | DSpace |
| description | International Journal of Advanced Pervasive and Ubiquitous Computing, Vol 2, p.17 |
| format | Journal |
| id | oai:ir.oauife.edu.ng:123456789-5036 |
| institution | My University |
| language | English |
| publishDate | 2020 |
| publisher | International Journal of Advanced Pervasive and Ubiquitous Computing |
| record_format | dspace |
| spelling | oai:ir.oauife.edu.ng:123456789-50362023-05-13T11:12:32Z A Trust Model for Detecting Device Attacks in Mobile Ad Hoc Ambient Home Network Solomon, Akinboro Olajubu, Emmanuel Ogundoyin, Ibrahim Aderounmu, Ganiyu Ad Hoc Home Network Adaptive Neuro Fuzzy Ambient Device Attacks Trust Management International Journal of Advanced Pervasive and Ubiquitous Computing, Vol 2, p.17 This study designed, simulated and evaluated the performance of a conceptual framework for ambient ad hoc home network. This was with a view to detecting malicious nodes and securing the home devices against attacks. The proposed framework, called mobile ambient social trust consists of mobile devices and mobile ad hoc network as communication channel. The trust model for the device attacks is Adaptive Neuro Fuzzy (ANF) that considered global reputation of the direct and indirect communication of home devices and remote devices. The model was simulated using Matlab 7.0. In the simulation, NSL-KDD dataset was used as input packets, the artificial neural network for packet classification and ANF system for the global trust computation. The proposed model was benchmarked with an existing Eigen Trust (ET) model using detection accuracy and convergence time as performance metrics. The simulation results using the above parameters revealed a better performance of the ANF over ET model. The framework will secure the home network against unforeseen network disruption and node misbehavior. 2020-01-15T10:03:00Z 2020-01-15T10:03:00Z 2016-06 Journal https://ir.oauife.edu.ng/handle/123456789/5036 en application/pdf International Journal of Advanced Pervasive and Ubiquitous Computing |
| spellingShingle | Ad Hoc Home Network Adaptive Neuro Fuzzy Ambient Device Attacks Trust Management Solomon, Akinboro Olajubu, Emmanuel Ogundoyin, Ibrahim Aderounmu, Ganiyu A Trust Model for Detecting Device Attacks in Mobile Ad Hoc Ambient Home Network |
| title | A Trust Model for Detecting Device Attacks in Mobile Ad Hoc Ambient Home Network |
| title_full | A Trust Model for Detecting Device Attacks in Mobile Ad Hoc Ambient Home Network |
| title_fullStr | A Trust Model for Detecting Device Attacks in Mobile Ad Hoc Ambient Home Network |
| title_full_unstemmed | A Trust Model for Detecting Device Attacks in Mobile Ad Hoc Ambient Home Network |
| title_short | A Trust Model for Detecting Device Attacks in Mobile Ad Hoc Ambient Home Network |
| title_sort | trust model for detecting device attacks in mobile ad hoc ambient home network |
| topic | Ad Hoc Home Network Adaptive Neuro Fuzzy Ambient Device Attacks Trust Management |
| url | https://ir.oauife.edu.ng/handle/123456789/5036 |
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