PQClass: Classification of Post-Quantum Encryption Applications in Internet Traffic

Post-quantum cryptography (PQC) is expected to revolutionize secure communications in next-generation digital ecosystems. Previous and ongoing activities demonstrate that different PQC algorithms significantly impact traffic latency, but they do not yet provide a scheme to assess the existence of the PQC algorithm or its identification when encrypted traffic is analyzed for traffic engineering purposes. Hence, this work is the first to propose a novel PQClass pipeline for classifying encrypted Internet traffic of recently NIST-approved PQC algorithms. Hence, it establishes solid grounds for enabling engineers to optimize their networks and, in parallel, for cybersecurity practitioners to familiarise themselves with PQC algorithmic properties for enhancing or devising security architectures in diverse setups. Our pipeline demonstrates impressive performance on real-world data, achieving 86% accuracy in detecting the presence of a PQC algorithm and 91% and 98% accuracy in identifying the browser and OS, respectively, based on PQC-based traffic.

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Publication Details

Published
2025-06-08
DOI
https://doi.org/10.1109/icc52391.2025.11160818
Primary Topic
Internet Traffic Analysis and Secure E-voting
Type
article
Field-Weighted Citation Impact
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article

PQClass: Classification of Post-Quantum Encryption Applications in Internet Traffic

Angelos K. Marnerides, Chen Hajaj, Ran Dubin, Amit Dvir et al.
Internet Traffic Analysis and Secure E-voting
article

PQClass: Classification of Post-Quantum Encryption Applications in Internet Traffic

Angelos K. Marnerides, Chen Hajaj, Ran Dubin, Amit Dvir, Revital Marbel
article en

Abstract

Post-quantum cryptography (PQC) is expected to revolutionize secure communications in next-generation digital ecosystems. Previous and ongoing activities demonstrate that different PQC algorithms significantly impact traffic latency, but they do not yet provide a scheme to assess the existence of the PQC algorithm or its identification when encrypted traffic is analyzed for traffic engineering purposes. Hence, this work is the first to propose a novel PQClass pipeline for classifying encrypted Internet traffic of recently NIST-approved PQC algorithms. Hence, it establishes solid grounds for enabling engineers to optimize their networks and, in parallel, for cybersecurity practitioners to familiarise themselves with PQC algorithmic properties for enhancing or devising security architectures in diverse setups. Our pipeline demonstrates impressive performance on real-world data, achieving 86% accuracy in detecting the presence of a PQC algorithm and 91% and 98% accuracy in identifying the browser and OS, respectively, based on PQC-based traffic.

Holon Institute of Technology (IL), University of Cyprus (CY), Ariel University (IL)
Openalex Percentile: Top 86%
Internet Traffic Analysis and Secure E-voting
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PQClass: Classification of Post-Quantum Encryption Applications in Internet Traffic — Angelos K. Marnerides, Chen Hajaj, et al. · (2025) | TGRS Research Map | TGRS