A Secure and Trusted Communication Solution for Web 3.0 Based on Edge Intelligence
[EN] The rise of AI has positioned edge computing as a pivotal domain for deploying machine learning technologies, fostering agile processing, and enhancing network robustness and decision-making capabilities. This paper addresses the underexplored aspects of DDoS and phishing attacks, and precise d...
| Autores: | , , , |
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| Formato: | artículo |
| Fecha de publicación: | 2025 |
| País: | España |
| Recursos: | Universitat Politècnica de València (UPV) |
| Repositorio: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia |
| Idioma: | inglés |
| OAI Identifier: | oai:dnet:riunet______::57d0a23efefec69ba637277f3e219b1d |
| Acesso em linha: | https://riunet.upv.es/handle/10251/234588 |
| Access Level: | acceso embargado |
| Palavra-chave: | Accurate decision making Edge intelligence Incentive mechanism IoT security Trust-based edge devices Web 3.0 |
| Resumo: | [EN] The rise of AI has positioned edge computing as a pivotal domain for deploying machine learning technologies, fostering agile processing, and enhancing network robustness and decision-making capabilities. This paper addresses the underexplored aspects of DDoS and phishing attacks, and precise decision-making at network edge devices within blockchain-based frameworks. The contribution lies in proposing an incentive-based security mechanism to divert intruders from genuine routes. Legitimate devices conducting accurate decision-making are rewarded, enticing their participation in identifying false devices. A honeypot intrusion detection system attracts false devices, and real-time trust computation monitors communication devices. This approach is analyzed under security threats and network delays, demonstrating its efficacy compared to existing methods in safeguarding edge computing environments. |
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