Generalized Encrypted Traffic Classification Using Inter-Flow Signals

Fuente: arXiv
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Autores principales: Bianchi, Federica, Di Paolo, Edoardo, Spognardi, Angelo
Formato: Preprint
Publicado: 2025
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author Bianchi, Federica
Di Paolo, Edoardo
Spognardi, Angelo
author_facet Bianchi, Federica
Di Paolo, Edoardo
Spognardi, Angelo
contents In this paper, we present a novel encrypted traffic classification model that operates directly on raw PCAP data without requiring prior assumptions about traffic type. Unlike existing methods, it is generalizable across multiple classification tasks and leverages inter-flow signals - an innovative representation that captures temporal correlations and packet volume distributions across flows. Experimental results show that our model outperforms well-established methods in nearly every classification task and across most datasets, achieving up to 99% accuracy in some cases, demonstrating its robustness and adaptability.
format Preprint
id arxiv_https___arxiv_org_abs_2508_21558
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Generalized Encrypted Traffic Classification Using Inter-Flow Signals
Bianchi, Federica
Di Paolo, Edoardo
Spognardi, Angelo
Cryptography and Security
Networking and Internet Architecture
In this paper, we present a novel encrypted traffic classification model that operates directly on raw PCAP data without requiring prior assumptions about traffic type. Unlike existing methods, it is generalizable across multiple classification tasks and leverages inter-flow signals - an innovative representation that captures temporal correlations and packet volume distributions across flows. Experimental results show that our model outperforms well-established methods in nearly every classification task and across most datasets, achieving up to 99% accuracy in some cases, demonstrating its robustness and adaptability.
title Generalized Encrypted Traffic Classification Using Inter-Flow Signals
topic Cryptography and Security
Networking and Internet Architecture
url https://arxiv.org/abs/2508.21558