{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T11:26:59Z","timestamp":1775215619309,"version":"3.50.1"},"reference-count":31,"publisher":"Privacy Enhancing Technologies Symposium Advisory Board","issue":"2","license":[{"start":{"date-parts":[[2021,1,29]],"date-time":"2021-01-29T00:00:00Z","timestamp":1611878400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/3.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,4,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>We introduce Generative Adversarial Networks for Data-Limited Fingerprinting (GANDaLF), a new deep-learning-based technique to perform Website Fingerprinting (WF) on Tor traffic. In contrast to most earlier work on deep-learning for WF, GANDaLF is intended to work with few training samples, and achieves this goal through the use of a Generative Adversarial Network to generate a large set of \u201cfake\u201d data that helps to train a deep neural network in distinguishing between classes of actual training data. We evaluate GANDaLF in low-data scenarios including as few as 10 training instances per site, and in multiple settings, including fingerprinting of website index pages and fingerprinting of non-index pages within a site. GANDaLF achieves closed-world accuracy of 87% with just 20 instances per site (and 100 sites) in standard WF settings. In particular, GANDaLF can outperform Var-CNN and Triplet Fingerprinting (TF) across all settings in subpage fingerprinting. For example, GANDaLF outperforms TF by a 29% margin and Var-CNN by 38% for training sets using 20 instances per site.<\/jats:p>","DOI":"10.2478\/popets-2021-0029","type":"journal-article","created":{"date-parts":[[2021,4,6]],"date-time":"2021-04-06T21:02:18Z","timestamp":1617742938000},"page":"305-322","source":"Crossref","is-referenced-by-count":40,"title":["GANDaLF: GAN for Data-Limited Fingerprinting"],"prefix":"10.56553","volume":"2021","author":[{"given":"Se Eun","family":"Oh","sequence":"first","affiliation":[{"name":"University of Minnesota"}]},{"given":"Nate","family":"Mathews","sequence":"additional","affiliation":[{"name":"Rochester Institute of Technology"}]},{"given":"Mohammad Saidur","family":"Rahman","sequence":"additional","affiliation":[{"name":"Rochester Institute of Technology"}]},{"given":"Matthew","family":"Wright","sequence":"additional","affiliation":[{"name":"Rochester Institute of Technology"}]},{"given":"Nicholas","family":"Hopper","sequence":"additional","affiliation":[{"name":"University of Minnesota"}]}],"member":"35752","published-online":{"date-parts":[[2021,1,29]]},"reference":[{"key":"2022043002462057908_j_popets-2021-0029_ref_001_w2aab3b7c32b1b6b1ab1ab1Aa","unstructured":"[1] Code for the paper \u201cimproved techniques for training GANs. https:\/\/github.com\/openai\/improved-gan."},{"key":"2022043002462057908_j_popets-2021-0029_ref_002_w2aab3b7c32b1b6b1ab1ab2Aa","unstructured":"[2] Does Alexa have a list of its top-ranked websites ? \u2013 Alexa support. https:\/\/support.alexa.com\/hc\/en-us\/articles\/200449834-Does-Alexa-have-a-list-of-its-top-ranked-websites-."},{"key":"2022043002462057908_j_popets-2021-0029_ref_003_w2aab3b7c32b1b6b1ab1ab3Aa","unstructured":"[3] Tor browser crawler. https:\/\/github.com\/webfp\/tor-browser-crawler."},{"key":"2022043002462057908_j_popets-2021-0029_ref_004_w2aab3b7c32b1b6b1ab1ab4Aa","doi-asserted-by":"crossref","unstructured":"[4] S. Bhat, D. Lu, A. Kwon, and S. Devadas. Var-CNN: A data-efficient website fingerprinting attack based on deep learning. Proceedings on Privacy Enhancing Technologies, 2019(4):292\u2013310, 2019.","DOI":"10.2478\/popets-2019-0070"},{"key":"2022043002462057908_j_popets-2021-0029_ref_005_w2aab3b7c32b1b6b1ab1ab5Aa","unstructured":"[5] I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio. Generative adversarial nets. In Advances in Neural Information Processing Systems (NeurIPS), pages 2672\u20132680, 2014."},{"key":"2022043002462057908_j_popets-2021-0029_ref_006_w2aab3b7c32b1b6b1ab1ab6Aa","unstructured":"[6] J. Hayes and G. Danezis. k-fingerprinting: A robust scalable website fingerprinting technique. In USENIX Security Symposium, pages 1187\u20131203, 2016."},{"key":"2022043002462057908_j_popets-2021-0029_ref_007_w2aab3b7c32b1b6b1ab1ab7Aa","doi-asserted-by":"crossref","unstructured":"[7] K. He, X. Zhang, S. Ren, and J. Sun. 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