1 // Copyright (c) 2012-2015 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 #include "bloom.h"
6 
7 #include "primitives/transaction.h"
8 #include "hash.h"
9 #include "script/script.h"
10 #include "script/standard.h"
11 #include "random.h"
12 #include "streams.h"
13 
14 #include <math.h>
15 #include <stdlib.h>
16 
17 #include <boost/foreach.hpp>
18 
19 #define LN2SQUARED 0.4804530139182014246671025263266649717305529515945455
20 #define LN2 0.6931471805599453094172321214581765680755001343602552
21 
22 using namespace std;
23 
CBloomFilter(unsigned int nElements,double nFPRate,unsigned int nTweakIn,unsigned char nFlagsIn)24 CBloomFilter::CBloomFilter(unsigned int nElements, double nFPRate, unsigned int nTweakIn, unsigned char nFlagsIn) :
25     /**
26      * The ideal size for a bloom filter with a given number of elements and false positive rate is:
27      * - nElements * log(fp rate) / ln(2)^2
28      * We ignore filter parameters which will create a bloom filter larger than the protocol limits
29      */
30     vData(min((unsigned int)(-1  / LN2SQUARED * nElements * log(nFPRate)), MAX_BLOOM_FILTER_SIZE * 8) / 8),
31     /**
32      * The ideal number of hash functions is filter size * ln(2) / number of elements
33      * Again, we ignore filter parameters which will create a bloom filter with more hash functions than the protocol limits
34      * See https://en.wikipedia.org/wiki/Bloom_filter for an explanation of these formulas
35      */
36     isFull(false),
37     isEmpty(false),
38     nHashFuncs(min((unsigned int)(vData.size() * 8 / nElements * LN2), MAX_HASH_FUNCS)),
39     nTweak(nTweakIn),
40     nFlags(nFlagsIn)
41 {
42 }
43 
44 // Private constructor used by CRollingBloomFilter
CBloomFilter(unsigned int nElements,double nFPRate,unsigned int nTweakIn)45 CBloomFilter::CBloomFilter(unsigned int nElements, double nFPRate, unsigned int nTweakIn) :
46     vData((unsigned int)(-1  / LN2SQUARED * nElements * log(nFPRate)) / 8),
47     isFull(false),
48     isEmpty(true),
49     nHashFuncs((unsigned int)(vData.size() * 8 / nElements * LN2)),
50     nTweak(nTweakIn),
51     nFlags(BLOOM_UPDATE_NONE)
52 {
53 }
54 
Hash(unsigned int nHashNum,const std::vector<unsigned char> & vDataToHash) const55 inline unsigned int CBloomFilter::Hash(unsigned int nHashNum, const std::vector<unsigned char>& vDataToHash) const
56 {
57     // 0xFBA4C795 chosen as it guarantees a reasonable bit difference between nHashNum values.
58     return MurmurHash3(nHashNum * 0xFBA4C795 + nTweak, vDataToHash) % (vData.size() * 8);
59 }
60 
insert(const vector<unsigned char> & vKey)61 void CBloomFilter::insert(const vector<unsigned char>& vKey)
62 {
63     if (isFull)
64         return;
65     for (unsigned int i = 0; i < nHashFuncs; i++)
66     {
67         unsigned int nIndex = Hash(i, vKey);
68         // Sets bit nIndex of vData
69         vData[nIndex >> 3] |= (1 << (7 & nIndex));
70     }
71     isEmpty = false;
72 }
73 
insert(const COutPoint & outpoint)74 void CBloomFilter::insert(const COutPoint& outpoint)
75 {
76     CDataStream stream(SER_NETWORK, PROTOCOL_VERSION);
77     stream << outpoint;
78     vector<unsigned char> data(stream.begin(), stream.end());
79     insert(data);
80 }
81 
insert(const uint256 & hash)82 void CBloomFilter::insert(const uint256& hash)
83 {
84     vector<unsigned char> data(hash.begin(), hash.end());
85     insert(data);
86 }
87 
contains(const vector<unsigned char> & vKey) const88 bool CBloomFilter::contains(const vector<unsigned char>& vKey) const
89 {
90     if (isFull)
91         return true;
92     if (isEmpty)
93         return false;
94     for (unsigned int i = 0; i < nHashFuncs; i++)
95     {
96         unsigned int nIndex = Hash(i, vKey);
97         // Checks bit nIndex of vData
98         if (!(vData[nIndex >> 3] & (1 << (7 & nIndex))))
99             return false;
100     }
101     return true;
102 }
103 
contains(const COutPoint & outpoint) const104 bool CBloomFilter::contains(const COutPoint& outpoint) const
105 {
106     CDataStream stream(SER_NETWORK, PROTOCOL_VERSION);
107     stream << outpoint;
108     vector<unsigned char> data(stream.begin(), stream.end());
109     return contains(data);
110 }
111 
contains(const uint256 & hash) const112 bool CBloomFilter::contains(const uint256& hash) const
113 {
114     vector<unsigned char> data(hash.begin(), hash.end());
115     return contains(data);
116 }
117 
clear()118 void CBloomFilter::clear()
119 {
120     vData.assign(vData.size(),0);
121     isFull = false;
122     isEmpty = true;
123 }
124 
reset(unsigned int nNewTweak)125 void CBloomFilter::reset(unsigned int nNewTweak)
126 {
127     clear();
128     nTweak = nNewTweak;
129 }
130 
IsWithinSizeConstraints() const131 bool CBloomFilter::IsWithinSizeConstraints() const
132 {
133     return vData.size() <= MAX_BLOOM_FILTER_SIZE && nHashFuncs <= MAX_HASH_FUNCS;
134 }
135 
IsRelevantAndUpdate(const CTransaction & tx)136 bool CBloomFilter::IsRelevantAndUpdate(const CTransaction& tx)
137 {
138     bool fFound = false;
139     // Match if the filter contains the hash of tx
140     //  for finding tx when they appear in a block
141     if (isFull)
142         return true;
143     if (isEmpty)
144         return false;
145     const uint256& hash = tx.GetHash();
146     if (contains(hash))
147         fFound = true;
148 
149     for (unsigned int i = 0; i < tx.vout.size(); i++)
150     {
151         const CTxOut& txout = tx.vout[i];
152         // Match if the filter contains any arbitrary script data element in any scriptPubKey in tx
153         // If this matches, also add the specific output that was matched.
154         // This means clients don't have to update the filter themselves when a new relevant tx
155         // is discovered in order to find spending transactions, which avoids round-tripping and race conditions.
156         CScript::const_iterator pc = txout.scriptPubKey.begin();
157         vector<unsigned char> data;
158         while (pc < txout.scriptPubKey.end())
159         {
160             opcodetype opcode;
161             if (!txout.scriptPubKey.GetOp(pc, opcode, data))
162                 break;
163             if (data.size() != 0 && contains(data))
164             {
165                 fFound = true;
166                 if ((nFlags & BLOOM_UPDATE_MASK) == BLOOM_UPDATE_ALL)
167                     insert(COutPoint(hash, i));
168                 else if ((nFlags & BLOOM_UPDATE_MASK) == BLOOM_UPDATE_P2PUBKEY_ONLY)
169                 {
170                     txnouttype type;
171                     vector<vector<unsigned char> > vSolutions;
172                     if (Solver(txout.scriptPubKey, type, vSolutions) &&
173                             (type == TX_PUBKEY || type == TX_MULTISIG))
174                         insert(COutPoint(hash, i));
175                 }
176                 break;
177             }
178         }
179     }
180 
181     if (fFound)
182         return true;
183 
184     BOOST_FOREACH(const CTxIn& txin, tx.vin)
185     {
186         // Match if the filter contains an outpoint tx spends
187         if (contains(txin.prevout))
188             return true;
189 
190         // Match if the filter contains any arbitrary script data element in any scriptSig in tx
191         CScript::const_iterator pc = txin.scriptSig.begin();
192         vector<unsigned char> data;
193         while (pc < txin.scriptSig.end())
194         {
195             opcodetype opcode;
196             if (!txin.scriptSig.GetOp(pc, opcode, data))
197                 break;
198             if (data.size() != 0 && contains(data))
199                 return true;
200         }
201     }
202 
203     return false;
204 }
205 
UpdateEmptyFull()206 void CBloomFilter::UpdateEmptyFull()
207 {
208     bool full = true;
209     bool empty = true;
210     for (unsigned int i = 0; i < vData.size(); i++)
211     {
212         full &= vData[i] == 0xff;
213         empty &= vData[i] == 0;
214     }
215     isFull = full;
216     isEmpty = empty;
217 }
218 
CRollingBloomFilter(unsigned int nElements,double fpRate)219 CRollingBloomFilter::CRollingBloomFilter(unsigned int nElements, double fpRate)
220 {
221     double logFpRate = log(fpRate);
222     /* The optimal number of hash functions is log(fpRate) / log(0.5), but
223      * restrict it to the range 1-50. */
224     nHashFuncs = std::max(1, std::min((int)round(logFpRate / log(0.5)), 50));
225     /* In this rolling bloom filter, we'll store between 2 and 3 generations of nElements / 2 entries. */
226     nEntriesPerGeneration = (nElements + 1) / 2;
227     uint32_t nMaxElements = nEntriesPerGeneration * 3;
228     /* The maximum fpRate = pow(1.0 - exp(-nHashFuncs * nMaxElements / nFilterBits), nHashFuncs)
229      * =>          pow(fpRate, 1.0 / nHashFuncs) = 1.0 - exp(-nHashFuncs * nMaxElements / nFilterBits)
230      * =>          1.0 - pow(fpRate, 1.0 / nHashFuncs) = exp(-nHashFuncs * nMaxElements / nFilterBits)
231      * =>          log(1.0 - pow(fpRate, 1.0 / nHashFuncs)) = -nHashFuncs * nMaxElements / nFilterBits
232      * =>          nFilterBits = -nHashFuncs * nMaxElements / log(1.0 - pow(fpRate, 1.0 / nHashFuncs))
233      * =>          nFilterBits = -nHashFuncs * nMaxElements / log(1.0 - exp(logFpRate / nHashFuncs))
234      */
235     uint32_t nFilterBits = (uint32_t)ceil(-1.0 * nHashFuncs * nMaxElements / log(1.0 - exp(logFpRate / nHashFuncs)));
236     data.clear();
237     /* For each data element we need to store 2 bits. If both bits are 0, the
238      * bit is treated as unset. If the bits are (01), (10), or (11), the bit is
239      * treated as set in generation 1, 2, or 3 respectively.
240      * These bits are stored in separate integers: position P corresponds to bit
241      * (P & 63) of the integers data[(P >> 6) * 2] and data[(P >> 6) * 2 + 1]. */
242     data.resize(((nFilterBits + 63) / 64) << 1);
243     reset();
244 }
245 
246 /* Similar to CBloomFilter::Hash */
RollingBloomHash(unsigned int nHashNum,uint32_t nTweak,const std::vector<unsigned char> & vDataToHash)247 static inline uint32_t RollingBloomHash(unsigned int nHashNum, uint32_t nTweak, const std::vector<unsigned char>& vDataToHash) {
248     return MurmurHash3(nHashNum * 0xFBA4C795 + nTweak, vDataToHash);
249 }
250 
insert(const std::vector<unsigned char> & vKey)251 void CRollingBloomFilter::insert(const std::vector<unsigned char>& vKey)
252 {
253     if (nEntriesThisGeneration == nEntriesPerGeneration) {
254         nEntriesThisGeneration = 0;
255         nGeneration++;
256         if (nGeneration == 4) {
257             nGeneration = 1;
258         }
259         uint64_t nGenerationMask1 = -(uint64_t)(nGeneration & 1);
260         uint64_t nGenerationMask2 = -(uint64_t)(nGeneration >> 1);
261         /* Wipe old entries that used this generation number. */
262         for (uint32_t p = 0; p < data.size(); p += 2) {
263             uint64_t p1 = data[p], p2 = data[p + 1];
264             uint64_t mask = (p1 ^ nGenerationMask1) | (p2 ^ nGenerationMask2);
265             data[p] = p1 & mask;
266             data[p + 1] = p2 & mask;
267         }
268     }
269     nEntriesThisGeneration++;
270 
271     for (int n = 0; n < nHashFuncs; n++) {
272         uint32_t h = RollingBloomHash(n, nTweak, vKey);
273         int bit = h & 0x3F;
274         uint32_t pos = (h >> 6) % data.size();
275         /* The lowest bit of pos is ignored, and set to zero for the first bit, and to one for the second. */
276         data[pos & ~1] = (data[pos & ~1] & ~(((uint64_t)1) << bit)) | ((uint64_t)(nGeneration & 1)) << bit;
277         data[pos | 1] = (data[pos | 1] & ~(((uint64_t)1) << bit)) | ((uint64_t)(nGeneration >> 1)) << bit;
278     }
279 }
280 
insert(const uint256 & hash)281 void CRollingBloomFilter::insert(const uint256& hash)
282 {
283     vector<unsigned char> data(hash.begin(), hash.end());
284     insert(data);
285 }
286 
contains(const std::vector<unsigned char> & vKey) const287 bool CRollingBloomFilter::contains(const std::vector<unsigned char>& vKey) const
288 {
289     for (int n = 0; n < nHashFuncs; n++) {
290         uint32_t h = RollingBloomHash(n, nTweak, vKey);
291         int bit = h & 0x3F;
292         uint32_t pos = (h >> 6) % data.size();
293         /* If the relevant bit is not set in either data[pos & ~1] or data[pos | 1], the filter does not contain vKey */
294         if (!(((data[pos & ~1] | data[pos | 1]) >> bit) & 1)) {
295             return false;
296         }
297     }
298     return true;
299 }
300 
contains(const uint256 & hash) const301 bool CRollingBloomFilter::contains(const uint256& hash) const
302 {
303     vector<unsigned char> data(hash.begin(), hash.end());
304     return contains(data);
305 }
306 
reset()307 void CRollingBloomFilter::reset()
308 {
309     nTweak = GetRand(std::numeric_limits<unsigned int>::max());
310     nEntriesThisGeneration = 0;
311     nGeneration = 1;
312     for (std::vector<uint64_t>::iterator it = data.begin(); it != data.end(); it++) {
313         *it = 0;
314     }
315 }
316