git / moonbite-core / src/bloom.cpp · raw

// Copyright (c) 2012-2019 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 <math.h>#include <stdlib.h>#include <algorithm>#define LN2SQUARED 0.4804530139182014246671025263266649717305529515945455#define LN2 0.6931471805599453094172321214581765680755001343602552CBloomFilter::CBloomFilter(const unsigned int nElements, const double nFPRate, const 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(std::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     */    nHashFuncs(std::min((unsigned int)(vData.size() * 8 / nElements * LN2), MAX_HASH_FUNCS)),    nTweak(nTweakIn),    nFlags(nFlagsIn){}inline unsigned int CBloomFilter::Hash(unsigned int nHashNum, const std::vector<unsigned char>& 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 std::vector<unsigned char>& vKey){    if (vData.empty()) // Avoid divide-by-zero (CVE-2013-5700)        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));    }}void CBloomFilter::insert(const COutPoint& outpoint){    CDataStream stream(SER_NETWORK, PROTOCOL_VERSION);    stream << outpoint;    std::vector<unsigned char> data(stream.begin(), stream.end());    insert(data);}void CBloomFilter::insert(const uint256& hash){    std::vector<unsigned char> data(hash.begin(), hash.end());    insert(data);}bool CBloomFilter::contains(const std::vector<unsigned char>& vKey) const{    if (vData.empty()) // Avoid divide-by-zero (CVE-2013-5700)        return true;    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;    std::vector<unsigned char> data(stream.begin(), stream.end());    return contains(data);}bool CBloomFilter::contains(const uint256& hash) const{    std::vector<unsigned char> data(hash.begin(), hash.end());    return contains(data);}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 (vData.empty()) // zero-size = "match-all" filter        return true;    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();        std::vector<unsigned char> 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)                {                    std::vector<std::vector<unsigned char> > vSolutions;                    TxoutType type = Solver(txout.scriptPubKey, vSolutions);                    if (type == TxoutType::PUBKEY || type == TxoutType::MULTISIG) {                        insert(COutPoint(hash, i));                    }                }                break;            }        }    }    if (fFound)        return true;    for (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();        std::vector<unsigned char> 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;}CRollingBloomFilter::CRollingBloomFilter(const unsigned int nElements, const 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<unsigned char>& vDataToHash) {    return MurmurHash3(nHashNum * 0xFBA4C795 + nTweak, vDataToHash);}// A replacement for x % n. This assumes that x and n are 32bit integers, and x is a uniformly random distributed 32bit value// which should be the case for a good hash.// See https://lemire.me/blog/2016/06/27/a-fast-alternative-to-the-modulo-reduction/static inline uint32_t FastMod(uint32_t x, size_t n) {    return ((uint64_t)x * (uint64_t)n) >> 32;}void CRollingBloomFilter::insert(const std::vector<unsigned char>& vKey){    if (nEntriesThisGeneration == nEntriesPerGeneration) {        nEntriesThisGeneration = 0;        nGeneration++;        if (nGeneration == 4) {            nGeneration = 1;        }        uint64_t nGenerationMask1 = 0 - (uint64_t)(nGeneration & 1);        uint64_t nGenerationMask2 = 0 - (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;        /* FastMod works with the upper bits of h, so it is safe to ignore that the lower bits of h are already used for bit. */        uint32_t pos = FastMod(h, 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){    std::vector<unsigned char> vData(hash.begin(), hash.end());    insert(vData);}bool CRollingBloomFilter::contains(const std::vector<unsigned char>& vKey) const{    for (int n = 0; n < nHashFuncs; n++) {        uint32_t h = RollingBloomHash(n, nTweak, vKey);        int bit = h & 0x3F;        uint32_t pos = FastMod(h, 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{    std::vector<unsigned char> vData(hash.begin(), hash.end());    return contains(vData);}void CRollingBloomFilter::reset(){    nTweak = GetRand(std::numeric_limits<unsigned int>::max());    nEntriesThisGeneration = 0;    nGeneration = 1;    std::fill(data.begin(), data.end(), 0);}