# k-fingerprinting: a Robust Scalable Website Fingerprinting Technique

arXiv: https://arxiv.org/abs/1509.00789 · HTML: https://mlsanity.com/paper/1509.00789/

## Key facts

- Cited by 34 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 Sep 2015.

## Built on by (most cited first, 30 of 34)

- [ET-BERT: A Contextualized Datagram Representation with Pre-training Transformers for Encrypted Traffic Classification](https://mlsanity.com/paper/2202.06335/) (2022)
- [NetMamba: Efficient Network Traffic Classification via Pre-training Unidirectional Mamba](https://mlsanity.com/paper/2405.11449/) (2024)
- [TrafficGPT: Breaking the Token Barrier for Efficient Long Traffic Analysis and Generation](https://mlsanity.com/paper/2403.05822/) (2024)
- [TFE-GNN: A Temporal Fusion Encoder Using Graph Neural Networks for Fine-grained Encrypted Traffic Classification](https://mlsanity.com/paper/2307.16713/) (2023)
- [Remote Timing Attacks on Efficient Language Model Inference](https://mlsanity.com/paper/2410.17175/) (2024)
- [Realistic Website Fingerprinting By Augmenting Network Trace](https://mlsanity.com/paper/2309.10147/) (2023)
- [Exposing LLM User Privacy via Traffic Fingerprint Analysis: A Study of Privacy Risks in LLM Agent Interactions](https://mlsanity.com/paper/2510.07176/) (2025)
- [Robust and Reliable Early-Stage Website Fingerprinting Attacks via Spatial-Temporal Distribution Analysis](https://mlsanity.com/paper/2407.00918/) (2024)
- [TrapFlow: Controllable Website Fingerprinting Defense via Dynamic Backdoor Learning](https://mlsanity.com/paper/2412.11471/) (2024)
- [Network-Level Prompt and Trait Leakage in Local Research Agents](https://mlsanity.com/paper/2508.20282/) (2025)
- [Efficient and Low Overhead Website Fingerprinting Attacks and Defenses based on TCP/IP Traffic](https://mlsanity.com/paper/2302.13763/) (2023)
- [Revisiting Backdoor Attacks on Time Series Classification in the Frequency Domain](https://mlsanity.com/paper/2503.09712/) (2025)
- [Towards Fine-Grained Webpage Fingerprinting at Scale](https://mlsanity.com/paper/2409.04341/) (2024)
- [Revolutionizing Encrypted Traffic Classification with MH-Net: A Multi-View Heterogeneous Graph Model](https://mlsanity.com/paper/2501.03279/) (2025)
- [STAR: Semantic-Traffic Alignment and Retrieval for Zero-Shot HTTPS Website Fingerprinting](https://mlsanity.com/paper/2512.17667/) (2025)
- [ResAware: Cross-Environment Website Fingerprinting via Resource-Privileged Distillation](https://mlsanity.com/paper/2606.17462/) (2026)
- [Website fingerprinting on early QUIC traffic](https://mlsanity.com/paper/2101.11871/) (2021)
- [One Train for Two Tasks: An Encrypted Traffic Classification Framework Using Supervised Contrastive Learning](https://mlsanity.com/paper/2402.07501/) (2024)
- [UniNet: A Unified Multi-granular Traffic Modeling Framework for Network Security](https://mlsanity.com/paper/2503.04174/) (2025)
- [NetMamba+: A Framework of Pre-trained Models for Efficient and Accurate Network Traffic Classification](https://mlsanity.com/paper/2601.21792/) (2026)
- [UniAlign: A Model-Agnostic Framework for Robust Network Traffic Classification under Distribution Shifts](https://mlsanity.com/paper/2605.17575/) (2026)
- [From Privacy to Workflow Integrity: Communication-Graph Metadata in Autonomous Agent Interoperability](https://mlsanity.com/paper/2606.07150/) (2026)
- [Whose Agent Are You? Multi-Layer Fingerprinting and Attribution of Autonomous Web Agents](https://mlsanity.com/paper/2606.20910/) (2026)
- [A Large-Scale Benchmark and Risk Assessment of Traffic Analysis Attacks on Cloud LLM Services](https://mlsanity.com/paper/2609.31877/) (2026)
- [Neural-FacTOR: Neural Representation Learning for Website Fingerprinting Attack over TOR Anonymity](https://mlsanity.com/paper/2209.12482/) (2022)
- [Representation Learning of Tangled Key-Value Sequence Data for Early Classification](https://mlsanity.com/paper/2404.07454/) (2024)
- [Examining the Rat in the Tunnel: Interpretable Multi-Label Classification of Tor-based Malware](https://mlsanity.com/paper/2409.16639/) (2024)
- [PacketCLIP: Multi-Modal Embedding of Network Traffic and Language for Cybersecurity Reasoning](https://mlsanity.com/paper/2503.03747/) (2025)
- [Attack Smarter: Attention-Driven Fine-Grained Webpage Fingerprinting Attacks](https://mlsanity.com/paper/2506.20082/) (2025)
- [Taming Data Challenges in ML-based Security Tasks Using Generative AI](https://mlsanity.com/paper/2507.06092/) (2025)

## Abstract (arXiv)

Website fingerprinting enables an attacker to infer which web page a client is browsing through encrypted or anonymized network connections. We present a new website fingerprinting technique based on random decision forests and evaluate performance over standard web pages as well as Tor hidden services, on a larger scale than previous works. Our technique, k-fingerprinting, performs better than current state-of-the-art attacks even against website fingerprinting defenses, and we show that it is possible to launch a website fingerprinting attack in the face of a large amount of noisy data. We can correctly determine which of 30 monitored hidden services a client is visiting with 85% true positive rate (TPR), a false positive rate (FPR) as low as 0.02%, from a world size of 100,000 unmonitored web pages. We further show that error rates vary widely between web resources, and thus some patterns of use will be predictably more vulnerable to attack than others.