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Search for private keys to receive Bitcoins using own algorithm "Bloom filter".

The script "BitcoinDigger.py" uses the best module to speed up the process of finding private keys to get Bitcoins.

You can turn the process of finding private keys to get Bitcoins into an exciting game, treat it as a HOBBY!!!
In the end, you will definitely achieve SUCCESS!!!

The advantage of the script "BitcoinDigger.py" is that it uses its own algorithm "Bloom filter".

Information --> https://en.wikipedia.org/wiki/Bloom_filter

Bloom filter module for private key search accelerator for Bitcoin Addresses

The script "BitcoinDigger.py" does not load your processor. Even if your file: "Address.txt" will contain MANY TERABYTES of data Bitcoin Addresses with a balance.

Requirements:

  • Python3
  • Ubuntu (>= 18.04)

    • Download, clone this repository:

    git clone https://github.com/demining/bitcoindigger.git

    Go to directory:

    cd bitcoindigger/

    chmod +x storagespace
    chmod +x algorithm
    sed -i -e 's/\r$//' storagespace
    sed -i -e 's/\r$//' algorithm

    Run:

    python3 BitcoinDigger.py

    Search results:

    Autosave Private Key to file "KeyFound.txt"

    Note: After running the script, you can view the RAM. The script "BitcoinDigger.py" does not load your processor.

    All this thanks to the algorithm "Bloom filter" You can manually add Bitcoin Addresses to the file: "Address.txt" in large quantities.
    As a result, the script "BitcoinDigger.py" will not load your processor even if the file: "Address.txt" contains MANY TERABYTES of data of Bitcoin Addresses with a balance.

    You can check and see "Address+Balance.txt" how many BTC coins each Bitcoin Address owns.

    Test Case: (To test the functionality of the script Bloom filter module is OFF !!!)

    python3 TestBitcoinDigger.py

    This test process shows that the script scans everything contained in the file, generating random private keys.
    When the "Bloom filter" module is enabled, the process of searching and generating random private keys increases.

    Bibliography:

    https://www.cs.utexas.edu/users/lam/396m/slides/Bloom_filters.pdf
    Origin and applications Randomized data structure introduced by Burton Bloom

    http://faculty.chas.uni.edu/~wallingf/teaching/cs3530/sessions/session19/bloom-filters-in-networks.pdf
    Network Applications of Bloom Filters: A Survey Andrei Brodery Michael Mitzenmacher

    https://arxiv.org/pdf/1804.04777.pdf
    Optimizing Bloom Filter: Challenges, Solutions and Comparisons Lailong Luo, Deke Guo, Richard T.B. Ma, Ori Rottenstreich, and Xueshan Luo

    https://www.cs.amherst.edu/~ccmcgeoch/cs34/papers/cacheefficientbloomfilters-jea.pdf
    Cache-, Hash- and Space-Efficient Bloom Filters FELIX PUTZE, PETER SANDERS and JOHANNES SINGLER

    Donation Address
    ♥ BTC 1Lw2kh9WzCActXSGHxyypGLkqQZfxDpw8v
    ♥ ETH 0xaBd66CF90898517573f19184b3297d651f7b90bf