Trust Model for Underwater Wireless Sensor Networks Based on Variational Autoencoders
In underwater wireless sensor networks(UWSNs), the complex underwater acoustic communication environment and the limited resources of nodes make malicious node attacks more covert and threatening. Therefore, researching effective malicious node detection methods is crucial for maintaining network st...
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Science Press (China)
2025-04-01
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| Series: | 水下无人系统学报 |
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| Online Access: | https://sxwrxtxb.xml-journal.net/cn/article/doi/10.11993/j.issn.2096-3920.2024-0181 |
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| author | Jiahao ZHANG Sizhou WEI Na XIA |
| author_facet | Jiahao ZHANG Sizhou WEI Na XIA |
| author_sort | Jiahao ZHANG |
| collection | DOAJ |
| description | In underwater wireless sensor networks(UWSNs), the complex underwater acoustic communication environment and the limited resources of nodes make malicious node attacks more covert and threatening. Therefore, researching effective malicious node detection methods is crucial for maintaining network stability and data security. This paper proposed a trust model for UWSNs based on variational autoencoders(VAEs), which evaluated node behavior credibility to identify malicious nodes. First, the model aggregated the behavioral feature data from the underwater node transmission process, extracting various indicators such as node location, packet delivery ratio, and delay, thereby forming a trust dataset. The dataset was then encoded and trained, and variational inference was employed to map the data to a latent space and obtain the probability distribution of this space. Finally, based on the probability distribution, the model decoded and reconstructed the data to derive node behavior credibility, thus completing the trust evaluation of nodes. Comparative experimental results show that compared to methods such as the intrusion detection-based trust management system, the proposed model improves trust evaluation accuracy by at least 10.5% and demonstrates significant advantages in operational stability. |
| format | Article |
| id | doaj-art-7dfbd5e7662d4ceba1e541091f429b2a |
| institution | Kabale University |
| issn | 2096-3920 |
| language | zho |
| publishDate | 2025-04-01 |
| publisher | Science Press (China) |
| record_format | Article |
| series | 水下无人系统学报 |
| spelling | doaj-art-7dfbd5e7662d4ceba1e541091f429b2a2025-08-20T03:29:10ZzhoScience Press (China)水下无人系统学报2096-39202025-04-0133230731610.11993/j.issn.2096-3920.2024-01812024-0181Trust Model for Underwater Wireless Sensor Networks Based on Variational AutoencodersJiahao ZHANG0Sizhou WEI1Na XIA2School of Computer Science and Information Engineering, Hefei University of Technology, Hefei 230000, ChinaSchool of Computer Science and Information Engineering, Hefei University of Technology, Hefei 230000, ChinaSchool of Computer Science and Information Engineering, Hefei University of Technology, Hefei 230000, ChinaIn underwater wireless sensor networks(UWSNs), the complex underwater acoustic communication environment and the limited resources of nodes make malicious node attacks more covert and threatening. Therefore, researching effective malicious node detection methods is crucial for maintaining network stability and data security. This paper proposed a trust model for UWSNs based on variational autoencoders(VAEs), which evaluated node behavior credibility to identify malicious nodes. First, the model aggregated the behavioral feature data from the underwater node transmission process, extracting various indicators such as node location, packet delivery ratio, and delay, thereby forming a trust dataset. The dataset was then encoded and trained, and variational inference was employed to map the data to a latent space and obtain the probability distribution of this space. Finally, based on the probability distribution, the model decoded and reconstructed the data to derive node behavior credibility, thus completing the trust evaluation of nodes. Comparative experimental results show that compared to methods such as the intrusion detection-based trust management system, the proposed model improves trust evaluation accuracy by at least 10.5% and demonstrates significant advantages in operational stability.https://sxwrxtxb.xml-journal.net/cn/article/doi/10.11993/j.issn.2096-3920.2024-0181underwater wireless sensor networktrust modelvariational autoencoder |
| spellingShingle | Jiahao ZHANG Sizhou WEI Na XIA Trust Model for Underwater Wireless Sensor Networks Based on Variational Autoencoders 水下无人系统学报 underwater wireless sensor network trust model variational autoencoder |
| title | Trust Model for Underwater Wireless Sensor Networks Based on Variational Autoencoders |
| title_full | Trust Model for Underwater Wireless Sensor Networks Based on Variational Autoencoders |
| title_fullStr | Trust Model for Underwater Wireless Sensor Networks Based on Variational Autoencoders |
| title_full_unstemmed | Trust Model for Underwater Wireless Sensor Networks Based on Variational Autoencoders |
| title_short | Trust Model for Underwater Wireless Sensor Networks Based on Variational Autoencoders |
| title_sort | trust model for underwater wireless sensor networks based on variational autoencoders |
| topic | underwater wireless sensor network trust model variational autoencoder |
| url | https://sxwrxtxb.xml-journal.net/cn/article/doi/10.11993/j.issn.2096-3920.2024-0181 |
| work_keys_str_mv | AT jiahaozhang trustmodelforunderwaterwirelesssensornetworksbasedonvariationalautoencoders AT sizhouwei trustmodelforunderwaterwirelesssensornetworksbasedonvariationalautoencoders AT naxia trustmodelforunderwaterwirelesssensornetworksbasedonvariationalautoencoders |