Line data    Source code

       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