// Copyright (c) 2012-2015 The Bitcoin Core developers // Distributed under the MIT software license, see the accompanying // file COPYING or http://www.opensource.org/licenses/mit-license.php. #ifndef BITCOIN_BLOOM_H #define BITCOIN_BLOOM_H #include #include class COutPoint; class CScript; class CTransaction; class uint256; class uint160; //! 20,000 items with fp rate < 0.1% or 10,000 items and <0.0001% static const unsigned int MAX_BLOOM_FILTER_SIZE = 36000; // bytes static const unsigned int MAX_HASH_FUNCS = 50; /** * First two bits of nFlags control how much IsRelevantAndUpdate actually updates * The remaining bits are reserved */ enum bloomflags { BLOOM_UPDATE_NONE = 0, BLOOM_UPDATE_ALL = 1, // Only adds outpoints to the filter if the output is a pay-to-pubkey/pay-to-multisig script BLOOM_UPDATE_P2PUBKEY_ONLY = 2, BLOOM_UPDATE_MASK = 3, }; /** * BloomFilter is a probabilistic filter which SPV clients provide * so that we can filter the transactions we send them. * * This allows for significantly more efficient transaction and block downloads. * * Because bloom filters are probabilistic, a SPV node can increase the false- * positive rate, making us send it transactions which aren't actually its, * allowing clients to trade more bandwidth for more privacy by obfuscating which * keys are controlled by them. */ class CBloomFilter { private: std::vector vData; bool isFull; bool isEmpty; unsigned int nHashFuncs; unsigned int nTweak; unsigned char nFlags; unsigned int Hash(unsigned int nHashNum, const std::vector& vDataToHash) const; // Check matches for arbitrary script data elements bool CheckScript(const CScript& script) const; // Check additional matches for special transactions bool CheckSpecialTransactionMatchesAndUpdate(const CTransaction& tx); public: /** * Creates a new bloom filter which will provide the given fp rate when filled with the given number of elements * Note that if the given parameters will result in a filter outside the bounds of the protocol limits, * the filter created will be as close to the given parameters as possible within the protocol limits. * This will apply if nFPRate is very low or nElements is unreasonably high. * nTweak is a constant which is added to the seed value passed to the hash function * It should generally always be a random value (and is largely only exposed for unit testing) * nFlags should be one of the BLOOM_UPDATE_* enums (not _MASK) */ CBloomFilter(const unsigned int nElements, const double nFPRate, const unsigned int nTweak, unsigned char nFlagsIn); CBloomFilter() : isFull(true), isEmpty(false), nHashFuncs(0), nTweak(0), nFlags(0) {} SERIALIZE_METHODS(CBloomFilter, obj) { READWRITE(obj.vData, obj.nHashFuncs, obj.nTweak, obj.nFlags); } void insert(const std::vector& vKey); void insert(const COutPoint& outpoint); void insert(const uint256& hash); bool contains(const std::vector& vKey) const; bool contains(const COutPoint& outpoint) const; bool contains(const uint256& hash) const; bool contains(const uint160& hash) const; void clear(); void reset(const unsigned int nNewTweak); //! True if the size is <= MAX_BLOOM_FILTER_SIZE and the number of hash functions is <= MAX_HASH_FUNCS //! (catch a filter which was just deserialized which was too big) bool IsWithinSizeConstraints() const; //! Also adds any outputs which match the filter to the filter (to match their spending txes) bool IsRelevantAndUpdate(const CTransaction& tx); //! Checks for empty and full filters to avoid wasting cpu void UpdateEmptyFull(); }; /** * RollingBloomFilter is a probabilistic "keep track of most recently inserted" set. * Construct it with the number of items to keep track of, and a false-positive * rate. Unlike CBloomFilter, by default nTweak is set to a cryptographically * secure random value for you. Similarly rather than clear() the method * reset() is provided, which also changes nTweak to decrease the impact of * false-positives. * * contains(item) will always return true if item was one of the last N to 1.5*N * insert()'ed ... but may also return true for items that were not inserted. * * It needs around 1.8 bytes per element per factor 0.1 of false positive rate. * For example, if we want 1000 elements, we'd need: * - ~1800 bytes for a false positive rate of 0.1 * - ~3600 bytes for a false positive rate of 0.01 * - ~5400 bytes for a false positive rate of 0.001 * * If we make these simplifying assumptions: * - logFpRate / log(0.5) doesn't get rounded or clamped in the nHashFuncs calculation * - nElements is even, so that nEntriesPerGeneration == nElements / 2 * * Then we get a more accurate estimate for filter bytes: * * 3/(log(256)*log(2)) * log(1/fpRate) * nElements */ class CRollingBloomFilter { public: // A random bloom filter calls GetRand() at creation time. // Don't create global CRollingBloomFilter objects, as they may be // constructed before the randomizer is properly initialized. CRollingBloomFilter(const unsigned int nElements, const double nFPRate); void insert(const std::vector& vKey); void insert(const uint256& hash); bool contains(const std::vector& vKey) const; bool contains(const uint256& hash) const; void reset(); private: int nEntriesPerGeneration; int nEntriesThisGeneration; int nGeneration; std::vector data; unsigned int nTweak; int nHashFuncs; }; #endif // BITCOIN_BLOOM_H