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@ -52,8 +52,8 @@ The malicious nodes can then capture the data of all packets that pass through t
With additional information, such as the names of the other routing nodes, it could infer who is making these payments, who is receiving them, and for what amounts. With additional information, such as the names of the other routing nodes, it could infer who is making these payments, who is receiving them, and for what amounts.
footnote:[Note that not all Lightning nodes are anonymous. footnote:[Note that not all Lightning nodes are anonymous.
It is known, for example, that the nodes "aantonop" and "1.ln.aantonop.com" are owned by the author of this book Andreas Antonopolous. It is known, for example, that the nodes "aantonop" and "1.ln.aantonop.com" are owned by the author of this book Andreas Antonopolous.
Furthermore, many companies and businesses in this space use a publicly known name for their routing nodes. Furthermore, companies and businesses in this space can claim ownership of a node by publicizing their node's alias and pubkey on their website or social media
If we see, for example, a payment with destination "Bitrefill", we could infer that someone is making a purchase from Bitrefill. If we see, for example, a payment with destination "Bitrefill" with a node pubkey that matches Bitrefill's publicized pubkey, we could infer that someone is making a purchase from Bitrefill.
If we know the prices of their services, we could even infer what they purchased. ] If we know the prices of their services, we could even infer what they purchased. ]
If it has multiple routing nodes connected to each other, it might even be responsible for transmitting several of the hops in a single payment and could form a more complete picture of the route. If it has multiple routing nodes connected to each other, it might even be responsible for transmitting several of the hops in a single payment and could form a more complete picture of the route.
We see this example as spiritually similar to the chain analysis already performed on the Bitcoin network; even an incomplete picture of payments can be used to infer things about the parties involved and potentially de-anonymize them. We see this example as spiritually similar to the chain analysis already performed on the Bitcoin network; even an incomplete picture of payments can be used to infer things about the parties involved and potentially de-anonymize them.