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1 : : // Copyright (c) 2012-2021 The Bitcoin Core developers 2 : : // Distributed under the MIT software license, see the accompanying 3 : : // file COPYING or http://www.opensource.org/licenses/mit-license.php. 4 : : 5 : : #ifndef BITCOIN_COMMON_BLOOM_H 6 : : #define BITCOIN_COMMON_BLOOM_H 7 : : 8 : : #include <serialize.h> 9 : : #include <span.h> 10 : : 11 : : #include <vector> 12 : : 13 : : class COutPoint; 14 : : class CTransaction; 15 : : 16 : : //! 20,000 items with fp rate < 0.1% or 10,000 items and <0.0001% 17 : : static constexpr unsigned int MAX_BLOOM_FILTER_SIZE = 36000; // bytes 18 : : static constexpr unsigned int MAX_HASH_FUNCS = 50; 19 : : 20 : : /** 21 : : * First two bits of nFlags control how much IsRelevantAndUpdate actually updates 22 : : * The remaining bits are reserved 23 : : */ 24 : : enum bloomflags 25 : : { 26 : : BLOOM_UPDATE_NONE = 0, 27 : : BLOOM_UPDATE_ALL = 1, 28 : : // Only adds outpoints to the filter if the output is a pay-to-pubkey/pay-to-multisig script 29 : : BLOOM_UPDATE_P2PUBKEY_ONLY = 2, 30 : : BLOOM_UPDATE_MASK = 3, 31 : : }; 32 : : 33 : : /** 34 : : * BloomFilter is a probabilistic filter which SPV clients provide 35 : : * so that we can filter the transactions we send them. 36 : : * 37 : : * This allows for significantly more efficient transaction and block downloads. 38 : : * 39 : : * Because bloom filters are probabilistic, a SPV node can increase the false- 40 : : * positive rate, making us send it transactions which aren't actually its, 41 : : * allowing clients to trade more bandwidth for more privacy by obfuscating which 42 : : * keys are controlled by them. 43 : : */ 44 : : class CBloomFilter 45 : : { 46 : : private: 47 : : std::vector<unsigned char> vData; 48 : : unsigned int nHashFuncs; 49 : : unsigned int nTweak; 50 : : unsigned char nFlags; 51 : : 52 : : unsigned int Hash(unsigned int nHashNum, Span<const unsigned char> vDataToHash) const; 53 : : 54 : : public: 55 : : /** 56 : : * Creates a new bloom filter which will provide the given fp rate when filled with the given number of elements 57 : : * Note that if the given parameters will result in a filter outside the bounds of the protocol limits, 58 : : * the filter created will be as close to the given parameters as possible within the protocol limits. 59 : : * This will apply if nFPRate is very low or nElements is unreasonably high. 60 : : * nTweak is a constant which is added to the seed value passed to the hash function 61 : : * It should generally always be a random value (and is largely only exposed for unit testing) 62 : : * nFlags should be one of the BLOOM_UPDATE_* enums (not _MASK) 63 : : */ 64 : : CBloomFilter(const unsigned int nElements, const double nFPRate, const unsigned int nTweak, unsigned char nFlagsIn); 65 : 0 : CBloomFilter() : nHashFuncs(0), nTweak(0), nFlags(0) {} 66 : : 67 : 0 : SERIALIZE_METHODS(CBloomFilter, obj) { READWRITE(obj.vData, obj.nHashFuncs, obj.nTweak, obj.nFlags); } 68 : : 69 : : void insert(Span<const unsigned char> vKey); 70 : : void insert(const COutPoint& outpoint); 71 : : 72 : : bool contains(Span<const unsigned char> vKey) const; 73 : : bool contains(const COutPoint& outpoint) const; 74 : : 75 : : //! True if the size is <= MAX_BLOOM_FILTER_SIZE and the number of hash functions is <= MAX_HASH_FUNCS 76 : : //! (catch a filter which was just deserialized which was too big) 77 : : bool IsWithinSizeConstraints() const; 78 : : 79 : : //! Also adds any outputs which match the filter to the filter (to match their spending txes) 80 : : bool IsRelevantAndUpdate(const CTransaction& tx); 81 : : }; 82 : : 83 : : /** 84 : : * RollingBloomFilter is a probabilistic "keep track of most recently inserted" set. 85 : : * Construct it with the number of items to keep track of, and a false-positive 86 : : * rate. Unlike CBloomFilter, by default nTweak is set to a cryptographically 87 : : * secure random value for you. Similarly rather than clear() the method 88 : : * reset() is provided, which also changes nTweak to decrease the impact of 89 : : * false-positives. 90 : : * 91 : : * contains(item) will always return true if item was one of the last N to 1.5*N 92 : : * insert()'ed ... but may also return true for items that were not inserted. 93 : : * 94 : : * It needs around 1.8 bytes per element per factor 0.1 of false positive rate. 95 : : * For example, if we want 1000 elements, we'd need: 96 : : * - ~1800 bytes for a false positive rate of 0.1 97 : : * - ~3600 bytes for a false positive rate of 0.01 98 : : * - ~5400 bytes for a false positive rate of 0.001 99 : : * 100 : : * If we make these simplifying assumptions: 101 : : * - logFpRate / log(0.5) doesn't get rounded or clamped in the nHashFuncs calculation 102 : : * - nElements is even, so that nEntriesPerGeneration == nElements / 2 103 : : * 104 : : * Then we get a more accurate estimate for filter bytes: 105 : : * 106 : : * 3/(log(256)*log(2)) * log(1/fpRate) * nElements 107 : : */ 108 : : class CRollingBloomFilter 109 : : { 110 : : public: 111 : : CRollingBloomFilter(const unsigned int nElements, const double nFPRate); 112 : : 113 : : void insert(Span<const unsigned char> vKey); 114 : : bool contains(Span<const unsigned char> vKey) const; 115 : : 116 : : void reset(); 117 : : 118 : : private: 119 : : int nEntriesPerGeneration; 120 : : int nEntriesThisGeneration; 121 : : int nGeneration; 122 : : std::vector<uint64_t> data; 123 : : unsigned int nTweak; 124 : : int nHashFuncs; 125 : : }; 126 : : 127 : : #endif // BITCOIN_COMMON_BLOOM_H