CBloomFilter Class Reference

BloomFilter is a probabilistic filter which SPV clients provide so that we can filter the transactions we send them. More...

#include <bloom.h>

Public Member Functions
	CBloomFilter (const uint32_t nElements, const double nFPRate, const uint32_t nTweak, uint8_t nFlagsIn)
	Creates a new bloom filter which will provide the given fp rate when filled with the given number of elements.
	CBloomFilter ()
	SERIALIZE_METHODS (CBloomFilter, obj)
void	insert (Span< const uint8_t > vKey)
void	insert (const COutPoint &outpoint)
bool	contains (Span< const uint8_t > vKey) const
bool	contains (const COutPoint &outpoint) const
bool	IsWithinSizeConstraints () const
	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	MatchAndInsertOutputs (const CTransaction &tx)
	Scans output scripts for matches and adds those outpoints to the filter for spend detection.
bool	MatchInputs (const CTransaction &tx)
	Scan inputs to see if the spent outpoints are a match, or the input scripts contain matching elements.
bool	IsRelevantAndUpdate (const CTransaction &tx)
	Check if the transaction is relevant for any reason.

Private Member Functions
uint32_t	Hash (uint32_t nHashNum, Span< const uint8_t > vDataToHash) const

Private Attributes
std::vector< uint8_t >	vData
uint32_t	nHashFuncs
uint32_t	nTweak
uint8_t	nFlags

Detailed Description

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.

Definition at line 44 of file bloom.h.

Constructor & Destructor Documentation

CBloomFilter() [1/2]

CBloomFilter::CBloomFilter	(	const uint32_t	nElements,
		const double	nFPRate,
		const uint32_t	nTweakIn,
		uint8_t	nFlagsIn
	)

Creates a new bloom filter which will provide the given fp rate when filled with the given number of elements.

The ideal size for a bloom filter with a given number of elements and false positive rate is:

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)

• nElements * log(fp rate) / ln(2)^2 We ignore filter parameters which will create a bloom filter larger than the protocol limits

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.

Definition at line 36 of file bloom.cpp.

CBloomFilter() [2/2]

CBloomFilter::CBloomFilter ( )

inline

Definition at line 67 of file bloom.h.

Member Function Documentation

contains() [1/2]

bool CBloomFilter::contains

(

const COutPoint &

outpoint

)

const

Definition at line 87 of file bloom.cpp.

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contains() [2/2]

bool CBloomFilter::contains

(

Span< const uint8_t >

vKey

)

const

Definition at line 72 of file bloom.cpp.

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Hash()

uint32_t CBloomFilter::Hash ( uint32_t  nHashNum, Span< const uint8_t >  vDataToHash  ) const

inlineprivate

Definition at line 45 of file bloom.cpp.

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insert() [1/2]

void CBloomFilter::insert

(

const COutPoint &

outpoint

)

Definition at line 66 of file bloom.cpp.

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insert() [2/2]

void CBloomFilter::insert

(

Span< const uint8_t >

vKey

)

Definition at line 53 of file bloom.cpp.

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IsRelevantAndUpdate()

bool CBloomFilter::IsRelevantAndUpdate ( const CTransaction &  tx )

inline

Check if the transaction is relevant for any reason.

Also adds any outputs which match the filter to the filter (to match their spending txes)

Definition at line 96 of file bloom.h.

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IsWithinSizeConstraints()

bool CBloomFilter::IsWithinSizeConstraints

(

)

const

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)

Definition at line 93 of file bloom.cpp.

MatchAndInsertOutputs()

bool CBloomFilter::MatchAndInsertOutputs

(

const CTransaction &

tx

)

Scans output scripts for matches and adds those outpoints to the filter for spend detection.

Returns true if any output matched, or the txid matches.

Definition at line 98 of file bloom.cpp.

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MatchInputs()

bool CBloomFilter::MatchInputs

(

const CTransaction &

tx

)

Scan inputs to see if the spent outpoints are a match, or the input scripts contain matching elements.

Definition at line 148 of file bloom.cpp.

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SERIALIZE_METHODS()

CBloomFilter::SERIALIZE_METHODS ( CBloomFilter  , obj    )

inline

Definition at line 69 of file bloom.h.

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Member Data Documentation

nFlags

uint8_t CBloomFilter::nFlags

private

Definition at line 49 of file bloom.h.

nHashFuncs

uint32_t CBloomFilter::nHashFuncs

private

Definition at line 47 of file bloom.h.

nTweak

uint32_t CBloomFilter::nTweak

private

Definition at line 48 of file bloom.h.

vData

std::vector<uint8_t> CBloomFilter::vData

private

Definition at line 46 of file bloom.h.

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The documentation for this class was generated from the following files:

• src/common/bloom.h
• src/common/bloom.cpp