A Graph Neural Network Approach for Identifying Decentralized Applications in Encrypted Traffic

Cryptographic network traffic classification has been challenged by the advent of decentralized applications (DApps), especially those based on blockchain platforms like Ethereum. It is difficult to identify DApps using traditional methods, such as port-based identification or deep packet inspection...

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Auteurs principaux:	Sufrianto Sufrianto, La Harudin, Abbas Oudah Waheed Alomairi, Mohammed Abdul Jaleel Maktoof
Format:	Artigo
Langue:	Inglês
Publié:	Anhalt University of Applied Sciences 2025-07-01
Collection:	Proceedings of the International Conference on Applied Innovations in IT
Sujets:	graph neural networks (gnns) encrypted traffic classification decentralized applications (dapps) traffic interaction graphs (tigs) network traffic analysis
Accès en ligne:	https://icaiit.org/paper.php?paper=13th_ICAIIT_3/4_4
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