X-PRINT:Platform-Agnostic and Scalable Fine-Grained Encrypted Traffic Fingerprinting
Fuente:
arXiv
Saved in:
| Main Authors: | , , , , , , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866909763077406720 |
|---|---|
| author | Zhu, YuKun Hua, ManYuan Huang, Hai Zhang, YongZhao Yang, Jie Xu, FengHua Chen, RuiDong Zhang, XiaoSong Yu, JiGuo Ma, Yong |
| author_facet | Zhu, YuKun Hua, ManYuan Huang, Hai Zhang, YongZhao Yang, Jie Xu, FengHua Chen, RuiDong Zhang, XiaoSong Yu, JiGuo Ma, Yong |
| contents | Although encryption protocols such as TLS are widely de-ployed,side-channel metadata in encrypted traffic still reveals patterns that allow application and behavior inference.How-ever,existing fine-grained fingerprinting approaches face two key limitations:(i)reliance on platform-dependent charac-teristics,which restricts generalization across heterogeneous platforms,and(ii)poor scalability for fine-grained behavior identification in open-world settings.
In this paper,we present X-PRINT,the first server-centric,URI-based framework for cross-platform fine-grained encrypted-traffic fingerprinting.X-PRINT systematically demonstrates that backend URI invocation patterns can serve as platform-agnostic invariants and are effective for mod-eling fine-grained behaviors.To achieve robust identifica-tion,X-PRINT further leverages temporally structured URI maps for behavior inference and emphasizes the exclusion of platform-or application-specific private URIs to handle unseen cases,thereby improving reliability in open-world and cross-platform settings.Extensive experiments across diverse cross-platform and open-world settings show that X-PRINT achieves state-of-the-art accuracy in fine-grained fingerprint-ing and exhibits strong scalability and robustness. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_00706 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | X-PRINT:Platform-Agnostic and Scalable Fine-Grained Encrypted Traffic Fingerprinting Zhu, YuKun Hua, ManYuan Huang, Hai Zhang, YongZhao Yang, Jie Xu, FengHua Chen, RuiDong Zhang, XiaoSong Yu, JiGuo Ma, Yong Cryptography and Security Although encryption protocols such as TLS are widely de-ployed,side-channel metadata in encrypted traffic still reveals patterns that allow application and behavior inference.How-ever,existing fine-grained fingerprinting approaches face two key limitations:(i)reliance on platform-dependent charac-teristics,which restricts generalization across heterogeneous platforms,and(ii)poor scalability for fine-grained behavior identification in open-world settings. In this paper,we present X-PRINT,the first server-centric,URI-based framework for cross-platform fine-grained encrypted-traffic fingerprinting.X-PRINT systematically demonstrates that backend URI invocation patterns can serve as platform-agnostic invariants and are effective for mod-eling fine-grained behaviors.To achieve robust identifica-tion,X-PRINT further leverages temporally structured URI maps for behavior inference and emphasizes the exclusion of platform-or application-specific private URIs to handle unseen cases,thereby improving reliability in open-world and cross-platform settings.Extensive experiments across diverse cross-platform and open-world settings show that X-PRINT achieves state-of-the-art accuracy in fine-grained fingerprint-ing and exhibits strong scalability and robustness. |
| title | X-PRINT:Platform-Agnostic and Scalable Fine-Grained Encrypted Traffic Fingerprinting |
| topic | Cryptography and Security |
| url | https://arxiv.org/abs/2509.00706 |