FAOACA-SND: Fuzzy selfish node detection employing arithmetic optimization algorithm and cell automata in DTN
In recent years, the number of smart devices has grown exponentially. However, the security and privacy of these devices are often neglected, which can lead to serious consequences. In this paper, we propose a method for detecting selfish nodes in DTN. Our method is based on analyzing the behavior o...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-02-01
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| Series: | Measurement: Sensors |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2665917423003331 |
| _version_ | 1797345907681787904 |
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| author | Rakhi Sharma Shail Kumar Dinkar |
| author_facet | Rakhi Sharma Shail Kumar Dinkar |
| author_sort | Rakhi Sharma |
| collection | DOAJ |
| description | In recent years, the number of smart devices has grown exponentially. However, the security and privacy of these devices are often neglected, which can lead to serious consequences. In this paper, we propose a method for detecting selfish nodes in DTN. Our method is based on analyzing the behavior of nodes in the network and identifying those that are not following the protocol. Cluster read selection using the hybrid optimized algorithm and cellular automata is used as the first phase of selfish node detection. The second phase uses fuzzy logic to categorize the nodes as selfish or cooperative. Fuzzy logic receives four network parameters from the simulation in MATLAB in a dynamic environment. The four network parameters are packet drop, average delay, residual energy, and nodes' reputations. The simulation results depict that the proposed method is a very accurate way to find selfish nodes. In the proposed mechanism, the proportion of false positives has decreased by 61.53 % compared to the existing mechanism. |
| first_indexed | 2024-03-08T11:24:35Z |
| format | Article |
| id | doaj.art-4099f91831854726ab647303b8ef7d08 |
| institution | Directory Open Access Journal |
| issn | 2665-9174 |
| language | English |
| last_indexed | 2024-03-08T11:24:35Z |
| publishDate | 2024-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Measurement: Sensors |
| spelling | doaj.art-4099f91831854726ab647303b8ef7d082024-01-26T05:35:00ZengElsevierMeasurement: Sensors2665-91742024-02-0131100997FAOACA-SND: Fuzzy selfish node detection employing arithmetic optimization algorithm and cell automata in DTNRakhi Sharma0Shail Kumar Dinkar1Department of Information Technology, Seth Jai Parkash Mukand Lal Institute of Engineering and Technology (JMIT), Radaur, Haryana, India; Department of Computer Science, Uttarakhand Technical University, Dehradun, India; Corresponding author. Department of Information Technology, Seth Jai Parkash Mukand Lal Institute of Engineering and Technology (JMIT), Radaur, Haryana, India.Department of Computer Science and Applications, Govind Ballabh Pant Institute of Engineering and Technology, Garhwal, Uttarakhand, IndiaIn recent years, the number of smart devices has grown exponentially. However, the security and privacy of these devices are often neglected, which can lead to serious consequences. In this paper, we propose a method for detecting selfish nodes in DTN. Our method is based on analyzing the behavior of nodes in the network and identifying those that are not following the protocol. Cluster read selection using the hybrid optimized algorithm and cellular automata is used as the first phase of selfish node detection. The second phase uses fuzzy logic to categorize the nodes as selfish or cooperative. Fuzzy logic receives four network parameters from the simulation in MATLAB in a dynamic environment. The four network parameters are packet drop, average delay, residual energy, and nodes' reputations. The simulation results depict that the proposed method is a very accurate way to find selfish nodes. In the proposed mechanism, the proportion of false positives has decreased by 61.53 % compared to the existing mechanism.http://www.sciencedirect.com/science/article/pii/S2665917423003331Delay tolerant network (DTN)Arithmetic optimization algorithmInternet of thingsSelfish nodesMamdani fuzzy systemCentrality |
| spellingShingle | Rakhi Sharma Shail Kumar Dinkar FAOACA-SND: Fuzzy selfish node detection employing arithmetic optimization algorithm and cell automata in DTN Measurement: Sensors Delay tolerant network (DTN) Arithmetic optimization algorithm Internet of things Selfish nodes Mamdani fuzzy system Centrality |
| title | FAOACA-SND: Fuzzy selfish node detection employing arithmetic optimization algorithm and cell automata in DTN |
| title_full | FAOACA-SND: Fuzzy selfish node detection employing arithmetic optimization algorithm and cell automata in DTN |
| title_fullStr | FAOACA-SND: Fuzzy selfish node detection employing arithmetic optimization algorithm and cell automata in DTN |
| title_full_unstemmed | FAOACA-SND: Fuzzy selfish node detection employing arithmetic optimization algorithm and cell automata in DTN |
| title_short | FAOACA-SND: Fuzzy selfish node detection employing arithmetic optimization algorithm and cell automata in DTN |
| title_sort | faoaca snd fuzzy selfish node detection employing arithmetic optimization algorithm and cell automata in dtn |
| topic | Delay tolerant network (DTN) Arithmetic optimization algorithm Internet of things Selfish nodes Mamdani fuzzy system Centrality |
| url | http://www.sciencedirect.com/science/article/pii/S2665917423003331 |
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