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Bloom Filters A bloom filter is a probabilistic search filter, a way to describe a desired pattern without specifying it exactly. Bloom filters offer an efficient way to express a search pattern while protecting privacy. They are used by SPV nodes to ask their peers for transactions matching a specific pattern, without revealing exactly which addresses they are search‐ ing for. In our previous analogy, a tourist without a map is asking for directions to a specific address “23 Church St”. If they asks strangers for directions to this street, they inadver‐ tently reveal their destination. A bloom filter is like asking “Are there any streets in this neighborhood whose name ends in R-C-H”. A question like that reveals slightly less about the desired destination, than asking for “23 Church St”. Using this technique, a tourist could specify the desired address in more detail as “ending in U-R-C-H” or less detail as “ending in H”. By varying the precision of the search, the tourist reveals more or less information, at the expense of getting more or less specific results. If they ask a less specific pattern, they get a lot more possible addresses and better privacy but many of the results are irrelevant. If they ask for a very specific pattern then they get fewer results but they lose privacy. Bloom filters serve this function by allowing an SPV node to specify a search pattern for transactions that can be tuned towards precision or privacy. A more specific bloom filter will produce accurate results, but at the expense of revealing what addresses are used in the user’s wallet. A less specific bloom filter will produce more data about more transactions, many irrelevant to the node, but will allow the node to maintain better privacy. An SPV node will initialize a bloom filter as “empty” and in that state the bloom filter will not match any patterns. The SPV node will then make a list of all the addresses in its wallet and create a search pattern matching the transaction output that corresponds to each address. Usually, the search pattern is a Pay-to-Public-Key-Hash script that is the expected locking script that will be present in any transaction paying to the public- key-hash (address). If the SPV node is tracking the balance of a P2SH address, then the search pattern will be a Pay-to-Script-Hash script, instead. The SPV node then adds each of the search patterns to the bloom filter, so that the bloom filter can recognize the search pattern if it is present in a transaction. Finally, the bloom filter is sent to the peer and the peer uses it to match transactions for transmission to the SPV node. Bloom filters are implemented as a variable-size array of N binary digits (a bit field) and a variable number of M hash functions. The hash functions are designed to always produce an output that is between 1 and N, corresponding to the array of binary digits. The hash functions are generated deterministically, so that any node implementing a bloom filter will always use the same hash functions and get the same results for a specific input. By choosing different length (N) bloom filters and a different number (M) of 154 | Chapter 6: The Bitcoin NetworkPDF Image | Mastering Bitcoin
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