36 lines
1.5 KiB
Markdown
36 lines
1.5 KiB
Markdown
In this section we will document simulations performed on the Email EU Core dataset (details below). In particular,
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we assess the worst-case scenario of a server with access to a sender-oracle (i.e. able to attribute tags to a
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particular sender) to understand how much information is leaked by fuzzytags without [appropriate deployment mitigations.](./deploying-fuzzytags.md)
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# Email EU Core Dataset Simulations
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Nodes: 1004
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Temporal Edges: 332334
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Time span: 803 days
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Citation: Ashwin Paranjape, Austin R. Benson, and Jure Leskovec. "Motifs in Temporal Networks." In Proceedings of the Tenth ACM International Conference on Web Search and Data Mining, 2017.
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![](./simulations/eu-actual.jpeg)
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## Scenario 1
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Setup: 1 month of email events between 1004 nodes, 20k events (5148 links). False positive rates: \[0.007812, 0.5\]. No entangling.
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Result: An adversarial server can identify ~7% of original graph (393 links) with a 6% false positive rate. Threshold: 0.0001
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![](./simulations/eu-derived.jpeg)
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## Scenario 2
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Setup: The same month of emails, 20k events (5148 links) Same false positive rates. Every tag is entangled with 1 random node.
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Result: Server can identify ~6.6% of original graph with a 6.8% false positive rate.
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![](./simulations/eu-derived-entangled.jpeg)
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# Discussion
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Entanglement seems to have some impact on the servers ability to relearn the social graph, in particular
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it increases the false positive rate of the derived graph. However, this impact is not significant enough in the
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observed simulation. |