// 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. #include "bloom.h" #include "primitives/transaction.h" #include "hash.h" #include "script/script.h" #include "script/standard.h" #include "random.h" #include "streams.h" #include #include #include #define LN2SQUARED 0.4804530139182014246671025263266649717305529515945455 #define LN2 0.6931471805599453094172321214581765680755001343602552 using namespace std; CBloomFilter::CBloomFilter(unsigned int nElements, double nFPRate, unsigned int nTweakIn, unsigned char nFlagsIn) : /** * The ideal size for a bloom filter with a given number of elements and false positive rate is: * - nElements * log(fp rate) / ln(2)^2 * We ignore filter parameters which will create a bloom filter larger than the protocol limits */ vData(min((unsigned int)(-1 / LN2SQUARED * nElements * log(nFPRate)), MAX_BLOOM_FILTER_SIZE * 8) / 8), /** * The ideal number of hash functions is filter size * ln(2) / number of elements * Again, we ignore filter parameters which will create a bloom filter with more hash functions than the protocol limits * See https://en.wikipedia.org/wiki/Bloom_filter for an explanation of these formulas */ isFull(false), isEmpty(true), nHashFuncs(min((unsigned int)(vData.size() * 8 / nElements * LN2), MAX_HASH_FUNCS)), nTweak(nTweakIn), nFlags(nFlagsIn) { } // Private constructor used by CRollingBloomFilter CBloomFilter::CBloomFilter(unsigned int nElements, double nFPRate, unsigned int nTweakIn) : vData((unsigned int)(-1 / LN2SQUARED * nElements * log(nFPRate)) / 8), isFull(false), isEmpty(true), nHashFuncs((unsigned int)(vData.size() * 8 / nElements * LN2)), nTweak(nTweakIn), nFlags(BLOOM_UPDATE_NONE) { } inline unsigned int CBloomFilter::Hash(unsigned int nHashNum, const std::vector& vDataToHash) const { // 0xFBA4C795 chosen as it guarantees a reasonable bit difference between nHashNum values. return MurmurHash3(nHashNum * 0xFBA4C795 + nTweak, vDataToHash) % (vData.size() * 8); } void CBloomFilter::insert(const vector& vKey) { if (isFull) return; for (unsigned int i = 0; i < nHashFuncs; i++) { unsigned int nIndex = Hash(i, vKey); // Sets bit nIndex of vData vData[nIndex >> 3] |= (1 << (7 & nIndex)); } isEmpty = false; } void CBloomFilter::insert(const COutPoint& outpoint) { CDataStream stream(SER_NETWORK, PROTOCOL_VERSION); stream << outpoint; vector data(stream.begin(), stream.end()); insert(data); } void CBloomFilter::insert(const uint256& hash) { vector data(hash.begin(), hash.end()); insert(data); } bool CBloomFilter::contains(const vector& vKey) const { if (isFull) return true; if (isEmpty) return false; for (unsigned int i = 0; i < nHashFuncs; i++) { unsigned int nIndex = Hash(i, vKey); // Checks bit nIndex of vData if (!(vData[nIndex >> 3] & (1 << (7 & nIndex)))) return false; } return true; } bool CBloomFilter::contains(const COutPoint& outpoint) const { CDataStream stream(SER_NETWORK, PROTOCOL_VERSION); stream << outpoint; vector data(stream.begin(), stream.end()); return contains(data); } bool CBloomFilter::contains(const uint256& hash) const { vector data(hash.begin(), hash.end()); return contains(data); } void CBloomFilter::clear() { vData.assign(vData.size(),0); isFull = false; isEmpty = true; } void CBloomFilter::reset(unsigned int nNewTweak) { clear(); nTweak = nNewTweak; } bool CBloomFilter::IsWithinSizeConstraints() const { return vData.size() <= MAX_BLOOM_FILTER_SIZE && nHashFuncs <= MAX_HASH_FUNCS; } bool CBloomFilter::IsRelevantAndUpdate(const CTransaction& tx) { bool fFound = false; // Match if the filter contains the hash of tx // for finding tx when they appear in a block if (isFull) return true; if (isEmpty) return false; const uint256& hash = tx.GetHash(); if (contains(hash)) fFound = true; for (unsigned int i = 0; i < tx.vout.size(); i++) { const CTxOut& txout = tx.vout[i]; // Match if the filter contains any arbitrary script data element in any scriptPubKey in tx // If this matches, also add the specific output that was matched. // This means clients don't have to update the filter themselves when a new relevant tx // is discovered in order to find spending transactions, which avoids round-tripping and race conditions. CScript::const_iterator pc = txout.scriptPubKey.begin(); vector data; while (pc < txout.scriptPubKey.end()) { opcodetype opcode; if (!txout.scriptPubKey.GetOp(pc, opcode, data)) break; if (data.size() != 0 && contains(data)) { fFound = true; if ((nFlags & BLOOM_UPDATE_MASK) == BLOOM_UPDATE_ALL) insert(COutPoint(hash, i)); else if ((nFlags & BLOOM_UPDATE_MASK) == BLOOM_UPDATE_P2PUBKEY_ONLY) { txnouttype type; vector > vSolutions; if (Solver(txout.scriptPubKey, type, vSolutions) && (type == TX_PUBKEY || type == TX_MULTISIG)) insert(COutPoint(hash, i)); } break; } } } if (fFound) return true; BOOST_FOREACH(const CTxIn& txin, tx.vin) { // Match if the filter contains an outpoint tx spends if (contains(txin.prevout)) return true; // Match if the filter contains any arbitrary script data element in any scriptSig in tx CScript::const_iterator pc = txin.scriptSig.begin(); vector data; while (pc < txin.scriptSig.end()) { opcodetype opcode; if (!txin.scriptSig.GetOp(pc, opcode, data)) break; if (data.size() != 0 && contains(data)) return true; } } return false; } void CBloomFilter::UpdateEmptyFull() { bool full = true; bool empty = true; for (unsigned int i = 0; i < vData.size(); i++) { full &= vData[i] == 0xff; empty &= vData[i] == 0; } isFull = full; isEmpty = empty; } CRollingBloomFilter::CRollingBloomFilter(unsigned int nElements, double fpRate) { double logFpRate = log(fpRate); /* The optimal number of hash functions is log(fpRate) / log(0.5), but * restrict it to the range 1-50. */ nHashFuncs = std::max(1, std::min((int)round(logFpRate / log(0.5)), 50)); /* In this rolling bloom filter, we'll store between 2 and 3 generations of nElements / 2 entries. */ nEntriesPerGeneration = (nElements + 1) / 2; uint32_t nMaxElements = nEntriesPerGeneration * 3; /* The maximum fpRate = pow(1.0 - exp(-nHashFuncs * nMaxElements / nFilterBits), nHashFuncs) * => pow(fpRate, 1.0 / nHashFuncs) = 1.0 - exp(-nHashFuncs * nMaxElements / nFilterBits) * => 1.0 - pow(fpRate, 1.0 / nHashFuncs) = exp(-nHashFuncs * nMaxElements / nFilterBits) * => log(1.0 - pow(fpRate, 1.0 / nHashFuncs)) = -nHashFuncs * nMaxElements / nFilterBits * => nFilterBits = -nHashFuncs * nMaxElements / log(1.0 - pow(fpRate, 1.0 / nHashFuncs)) * => nFilterBits = -nHashFuncs * nMaxElements / log(1.0 - exp(logFpRate / nHashFuncs)) */ uint32_t nFilterBits = (uint32_t)ceil(-1.0 * nHashFuncs * nMaxElements / log(1.0 - exp(logFpRate / nHashFuncs))); data.clear(); /* For each data element we need to store 2 bits. If both bits are 0, the * bit is treated as unset. If the bits are (01), (10), or (11), the bit is * treated as set in generation 1, 2, or 3 respectively. * These bits are stored in separate integers: position P corresponds to bit * (P & 63) of the integers data[(P >> 6) * 2] and data[(P >> 6) * 2 + 1]. */ data.resize(((nFilterBits + 63) / 64) << 1); reset(); } /* Similar to CBloomFilter::Hash */ static inline uint32_t RollingBloomHash(unsigned int nHashNum, uint32_t nTweak, const std::vector& vDataToHash) { return MurmurHash3(nHashNum * 0xFBA4C795 + nTweak, vDataToHash); } void CRollingBloomFilter::insert(const std::vector& vKey) { if (nEntriesThisGeneration == nEntriesPerGeneration) { nEntriesThisGeneration = 0; nGeneration++; if (nGeneration == 4) { nGeneration = 1; } uint64_t nGenerationMask1 = -(uint64_t)(nGeneration & 1); uint64_t nGenerationMask2 = -(uint64_t)(nGeneration >> 1); /* Wipe old entries that used this generation number. */ for (uint32_t p = 0; p < data.size(); p += 2) { uint64_t p1 = data[p], p2 = data[p + 1]; uint64_t mask = (p1 ^ nGenerationMask1) | (p2 ^ nGenerationMask2); data[p] = p1 & mask; data[p + 1] = p2 & mask; } } nEntriesThisGeneration++; for (int n = 0; n < nHashFuncs; n++) { uint32_t h = RollingBloomHash(n, nTweak, vKey); int bit = h & 0x3F; uint32_t pos = (h >> 6) % data.size(); /* The lowest bit of pos is ignored, and set to zero for the first bit, and to one for the second. */ data[pos & ~1] = (data[pos & ~1] & ~(((uint64_t)1) << bit)) | ((uint64_t)(nGeneration & 1)) << bit; data[pos | 1] = (data[pos | 1] & ~(((uint64_t)1) << bit)) | ((uint64_t)(nGeneration >> 1)) << bit; } } void CRollingBloomFilter::insert(const uint256& hash) { vector data(hash.begin(), hash.end()); insert(data); } bool CRollingBloomFilter::contains(const std::vector& vKey) const { for (int n = 0; n < nHashFuncs; n++) { uint32_t h = RollingBloomHash(n, nTweak, vKey); int bit = h & 0x3F; uint32_t pos = (h >> 6) % data.size(); /* If the relevant bit is not set in either data[pos & ~1] or data[pos | 1], the filter does not contain vKey */ if (!(((data[pos & ~1] | data[pos | 1]) >> bit) & 1)) { return false; } } return true; } bool CRollingBloomFilter::contains(const uint256& hash) const { vector data(hash.begin(), hash.end()); return contains(data); } void CRollingBloomFilter::reset() { nTweak = GetRand(std::numeric_limits::max()); nEntriesThisGeneration = 0; nGeneration = 1; for (std::vector::iterator it = data.begin(); it != data.end(); it++) { *it = 0; } }