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Binomial Random Walks and Bitcoin


Hitting probability of biased random walk on the integer lineRandom walks - two questionsrandom walks questionDouble Random WalksRandom walks and diffusion limitsIncrements in random walksSimple Random WalksThe probability behind Bitcoin.Relay channel: Multihop lower boundHow to convert a detailed mathematical, statistical compuational process into mathematical and statistical equation?GHOST selection rule for blockchain, proof of convergence of history













2












$begingroup$


In Satoshi Nakamoto's paper : Bitcoin: A Peer-to-Peer Electronic Cash System, he describes a scenario where an attacker is trying to add falsified transactions to the blockchain.



He writes : "The race between the honest chain and an attacker chain can be characterized as a Binomial Random Walk. The success event is the honest chain being extended by one block, increasing its lead by $+1$, and the failure event is the attacker's chain being extended by one block, reducing the gap by $-1$.



We can calculate the probability he ever
reaches break-even, or that an attacker ever catches up with the honest chain, as follows" :



Let $p = $ probability an honest node finds the next block



Let $q = $ probability the attacker finds the next block



Let $q_z = $ probability the attacker will ever catch up from $z$ blocks behind



And so $q_z = 1$ if $p leq q$, and $q_z = (q/p)^z$ if $p > q$.



I'm not sure how he arrived at this. Firstly, I have no idea why $q_z = 1$ if $p leq q$.



Secondly, from what I understand from a binomial distribution, the probability of the attacker catching up from $z$ blocks from behind should be equal
to $z choose z$ $q^z p^0 = q^z$. Any insights appreciated.










share|cite|improve this question











$endgroup$











  • $begingroup$
    These are results of simple random walks on $mathbbZ$. If you are more (or equally) likely to move right than move left, (with probability $1$) you will reach arbitrarily high values. Otherwise, the probability you ever reach $zinmathbbN$ units right of where you started is given by $(q/p)^z$, where $q$ is the probability of moving right on a step, and $p$ is the probability of moving left. See this for example for reading on simple random walks (beware that their $p$ and $q$ may be reversed from here though).
    $endgroup$
    – Minus One-Twelfth
    Mar 22 at 0:08











  • $begingroup$
    @MinusOne-Twelfth ok, I am not familiar with this topic and will do more research. If you post this as an answer I will accept it.
    $endgroup$
    – IntegrateThis
    Mar 22 at 0:11
















2












$begingroup$


In Satoshi Nakamoto's paper : Bitcoin: A Peer-to-Peer Electronic Cash System, he describes a scenario where an attacker is trying to add falsified transactions to the blockchain.



He writes : "The race between the honest chain and an attacker chain can be characterized as a Binomial Random Walk. The success event is the honest chain being extended by one block, increasing its lead by $+1$, and the failure event is the attacker's chain being extended by one block, reducing the gap by $-1$.



We can calculate the probability he ever
reaches break-even, or that an attacker ever catches up with the honest chain, as follows" :



Let $p = $ probability an honest node finds the next block



Let $q = $ probability the attacker finds the next block



Let $q_z = $ probability the attacker will ever catch up from $z$ blocks behind



And so $q_z = 1$ if $p leq q$, and $q_z = (q/p)^z$ if $p > q$.



I'm not sure how he arrived at this. Firstly, I have no idea why $q_z = 1$ if $p leq q$.



Secondly, from what I understand from a binomial distribution, the probability of the attacker catching up from $z$ blocks from behind should be equal
to $z choose z$ $q^z p^0 = q^z$. Any insights appreciated.










share|cite|improve this question











$endgroup$











  • $begingroup$
    These are results of simple random walks on $mathbbZ$. If you are more (or equally) likely to move right than move left, (with probability $1$) you will reach arbitrarily high values. Otherwise, the probability you ever reach $zinmathbbN$ units right of where you started is given by $(q/p)^z$, where $q$ is the probability of moving right on a step, and $p$ is the probability of moving left. See this for example for reading on simple random walks (beware that their $p$ and $q$ may be reversed from here though).
    $endgroup$
    – Minus One-Twelfth
    Mar 22 at 0:08











  • $begingroup$
    @MinusOne-Twelfth ok, I am not familiar with this topic and will do more research. If you post this as an answer I will accept it.
    $endgroup$
    – IntegrateThis
    Mar 22 at 0:11














2












2








2





$begingroup$


In Satoshi Nakamoto's paper : Bitcoin: A Peer-to-Peer Electronic Cash System, he describes a scenario where an attacker is trying to add falsified transactions to the blockchain.



He writes : "The race between the honest chain and an attacker chain can be characterized as a Binomial Random Walk. The success event is the honest chain being extended by one block, increasing its lead by $+1$, and the failure event is the attacker's chain being extended by one block, reducing the gap by $-1$.



We can calculate the probability he ever
reaches break-even, or that an attacker ever catches up with the honest chain, as follows" :



Let $p = $ probability an honest node finds the next block



Let $q = $ probability the attacker finds the next block



Let $q_z = $ probability the attacker will ever catch up from $z$ blocks behind



And so $q_z = 1$ if $p leq q$, and $q_z = (q/p)^z$ if $p > q$.



I'm not sure how he arrived at this. Firstly, I have no idea why $q_z = 1$ if $p leq q$.



Secondly, from what I understand from a binomial distribution, the probability of the attacker catching up from $z$ blocks from behind should be equal
to $z choose z$ $q^z p^0 = q^z$. Any insights appreciated.










share|cite|improve this question











$endgroup$




In Satoshi Nakamoto's paper : Bitcoin: A Peer-to-Peer Electronic Cash System, he describes a scenario where an attacker is trying to add falsified transactions to the blockchain.



He writes : "The race between the honest chain and an attacker chain can be characterized as a Binomial Random Walk. The success event is the honest chain being extended by one block, increasing its lead by $+1$, and the failure event is the attacker's chain being extended by one block, reducing the gap by $-1$.



We can calculate the probability he ever
reaches break-even, or that an attacker ever catches up with the honest chain, as follows" :



Let $p = $ probability an honest node finds the next block



Let $q = $ probability the attacker finds the next block



Let $q_z = $ probability the attacker will ever catch up from $z$ blocks behind



And so $q_z = 1$ if $p leq q$, and $q_z = (q/p)^z$ if $p > q$.



I'm not sure how he arrived at this. Firstly, I have no idea why $q_z = 1$ if $p leq q$.



Secondly, from what I understand from a binomial distribution, the probability of the attacker catching up from $z$ blocks from behind should be equal
to $z choose z$ $q^z p^0 = q^z$. Any insights appreciated.







probability






share|cite|improve this question















share|cite|improve this question













share|cite|improve this question




share|cite|improve this question








edited Mar 22 at 0:41









David G. Stork

12k41735




12k41735










asked Mar 21 at 23:50









IntegrateThisIntegrateThis

1,9401818




1,9401818











  • $begingroup$
    These are results of simple random walks on $mathbbZ$. If you are more (or equally) likely to move right than move left, (with probability $1$) you will reach arbitrarily high values. Otherwise, the probability you ever reach $zinmathbbN$ units right of where you started is given by $(q/p)^z$, where $q$ is the probability of moving right on a step, and $p$ is the probability of moving left. See this for example for reading on simple random walks (beware that their $p$ and $q$ may be reversed from here though).
    $endgroup$
    – Minus One-Twelfth
    Mar 22 at 0:08











  • $begingroup$
    @MinusOne-Twelfth ok, I am not familiar with this topic and will do more research. If you post this as an answer I will accept it.
    $endgroup$
    – IntegrateThis
    Mar 22 at 0:11

















  • $begingroup$
    These are results of simple random walks on $mathbbZ$. If you are more (or equally) likely to move right than move left, (with probability $1$) you will reach arbitrarily high values. Otherwise, the probability you ever reach $zinmathbbN$ units right of where you started is given by $(q/p)^z$, where $q$ is the probability of moving right on a step, and $p$ is the probability of moving left. See this for example for reading on simple random walks (beware that their $p$ and $q$ may be reversed from here though).
    $endgroup$
    – Minus One-Twelfth
    Mar 22 at 0:08











  • $begingroup$
    @MinusOne-Twelfth ok, I am not familiar with this topic and will do more research. If you post this as an answer I will accept it.
    $endgroup$
    – IntegrateThis
    Mar 22 at 0:11
















$begingroup$
These are results of simple random walks on $mathbbZ$. If you are more (or equally) likely to move right than move left, (with probability $1$) you will reach arbitrarily high values. Otherwise, the probability you ever reach $zinmathbbN$ units right of where you started is given by $(q/p)^z$, where $q$ is the probability of moving right on a step, and $p$ is the probability of moving left. See this for example for reading on simple random walks (beware that their $p$ and $q$ may be reversed from here though).
$endgroup$
– Minus One-Twelfth
Mar 22 at 0:08





$begingroup$
These are results of simple random walks on $mathbbZ$. If you are more (or equally) likely to move right than move left, (with probability $1$) you will reach arbitrarily high values. Otherwise, the probability you ever reach $zinmathbbN$ units right of where you started is given by $(q/p)^z$, where $q$ is the probability of moving right on a step, and $p$ is the probability of moving left. See this for example for reading on simple random walks (beware that their $p$ and $q$ may be reversed from here though).
$endgroup$
– Minus One-Twelfth
Mar 22 at 0:08













$begingroup$
@MinusOne-Twelfth ok, I am not familiar with this topic and will do more research. If you post this as an answer I will accept it.
$endgroup$
– IntegrateThis
Mar 22 at 0:11





$begingroup$
@MinusOne-Twelfth ok, I am not familiar with this topic and will do more research. If you post this as an answer I will accept it.
$endgroup$
– IntegrateThis
Mar 22 at 0:11











2 Answers
2






active

oldest

votes


















2












$begingroup$

These are results of simple random walks on $mathbbZ$. If you are more (or equally) likely to move right than move left, then you will with probability $1$ reach arbitrarily high values. Otherwise, the probability you ever reach $zinmathbbN$ units right of where you started is given by $(q/p)^z$, where $q$ is the probability of moving right on a step, and $p$ is the probability of moving left. See this for example for reading on simple random walks (beware that their $p$ and $q$ may be reversed from here though).






share|cite|improve this answer









$endgroup$




















    1












    $begingroup$


    I have no idea why $q_z=1$ if $ple q$.




    If $p<q$, then this follows simply from the Strong Law of Large Numbers. Let $X_i=+1$ if the hacker wins the $i^th$ block, and $X_i=-1$ if the honest node wins the $i^th$ block. Let $S_n=X_1+X_2+dots+X_n$. The SLLN implies that $S_n/n$ converges to the expected value of $X_i$, which is $q-p>0$. Since $S_n/n$ converges to a positive number, this means $S_n$ gets arbitrarily large, so the hacker will eventually exceed the honest node by any number (including $z$) of blocks.



    When $p=q$, you can instead use the Law of the Iterated logarithm to prove that $S_n$ gets arbitrarily large.




    from what I understand from a binomial distribution, the probability of the attacker catching up from z blocks from behind should be equal to $binomzz q^zp^0=q^z$.




    This is the probability they catch up after exactly $z$ blocks. We want the probability they eventually catch up, after any number of blocks. This is trickier to compute.



    For the probability when $z=1$, see Hitting probability of biased random walk on the integer line. The probability of eventually catching up from a deficit of $z$ is the same as the probability of catching up from a deficit of $1$, a total of $z$ times in a row. This lets you extend the $z=1$ case to general $z$.






    share|cite|improve this answer











    $endgroup$












    • $begingroup$
      Do you not mean let $X_i = -1$ ? Thanks for the answer.
      $endgroup$
      – IntegrateThis
      Mar 22 at 0:35










    • $begingroup$
      @IntegrateThis I meant what I wrote. Does something not make sense?
      $endgroup$
      – Mike Earnest
      Mar 22 at 0:44










    • $begingroup$
      My mistake. Thanks for the answer. I just reversed things in my head, oops.
      $endgroup$
      – IntegrateThis
      Mar 22 at 0:47












    Your Answer





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    2 Answers
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    2 Answers
    2






    active

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    active

    oldest

    votes






    active

    oldest

    votes









    2












    $begingroup$

    These are results of simple random walks on $mathbbZ$. If you are more (or equally) likely to move right than move left, then you will with probability $1$ reach arbitrarily high values. Otherwise, the probability you ever reach $zinmathbbN$ units right of where you started is given by $(q/p)^z$, where $q$ is the probability of moving right on a step, and $p$ is the probability of moving left. See this for example for reading on simple random walks (beware that their $p$ and $q$ may be reversed from here though).






    share|cite|improve this answer









    $endgroup$

















      2












      $begingroup$

      These are results of simple random walks on $mathbbZ$. If you are more (or equally) likely to move right than move left, then you will with probability $1$ reach arbitrarily high values. Otherwise, the probability you ever reach $zinmathbbN$ units right of where you started is given by $(q/p)^z$, where $q$ is the probability of moving right on a step, and $p$ is the probability of moving left. See this for example for reading on simple random walks (beware that their $p$ and $q$ may be reversed from here though).






      share|cite|improve this answer









      $endgroup$















        2












        2








        2





        $begingroup$

        These are results of simple random walks on $mathbbZ$. If you are more (or equally) likely to move right than move left, then you will with probability $1$ reach arbitrarily high values. Otherwise, the probability you ever reach $zinmathbbN$ units right of where you started is given by $(q/p)^z$, where $q$ is the probability of moving right on a step, and $p$ is the probability of moving left. See this for example for reading on simple random walks (beware that their $p$ and $q$ may be reversed from here though).






        share|cite|improve this answer









        $endgroup$



        These are results of simple random walks on $mathbbZ$. If you are more (or equally) likely to move right than move left, then you will with probability $1$ reach arbitrarily high values. Otherwise, the probability you ever reach $zinmathbbN$ units right of where you started is given by $(q/p)^z$, where $q$ is the probability of moving right on a step, and $p$ is the probability of moving left. See this for example for reading on simple random walks (beware that their $p$ and $q$ may be reversed from here though).







        share|cite|improve this answer












        share|cite|improve this answer



        share|cite|improve this answer










        answered Mar 22 at 0:11









        Minus One-TwelfthMinus One-Twelfth

        3,233413




        3,233413





















            1












            $begingroup$


            I have no idea why $q_z=1$ if $ple q$.




            If $p<q$, then this follows simply from the Strong Law of Large Numbers. Let $X_i=+1$ if the hacker wins the $i^th$ block, and $X_i=-1$ if the honest node wins the $i^th$ block. Let $S_n=X_1+X_2+dots+X_n$. The SLLN implies that $S_n/n$ converges to the expected value of $X_i$, which is $q-p>0$. Since $S_n/n$ converges to a positive number, this means $S_n$ gets arbitrarily large, so the hacker will eventually exceed the honest node by any number (including $z$) of blocks.



            When $p=q$, you can instead use the Law of the Iterated logarithm to prove that $S_n$ gets arbitrarily large.




            from what I understand from a binomial distribution, the probability of the attacker catching up from z blocks from behind should be equal to $binomzz q^zp^0=q^z$.




            This is the probability they catch up after exactly $z$ blocks. We want the probability they eventually catch up, after any number of blocks. This is trickier to compute.



            For the probability when $z=1$, see Hitting probability of biased random walk on the integer line. The probability of eventually catching up from a deficit of $z$ is the same as the probability of catching up from a deficit of $1$, a total of $z$ times in a row. This lets you extend the $z=1$ case to general $z$.






            share|cite|improve this answer











            $endgroup$












            • $begingroup$
              Do you not mean let $X_i = -1$ ? Thanks for the answer.
              $endgroup$
              – IntegrateThis
              Mar 22 at 0:35










            • $begingroup$
              @IntegrateThis I meant what I wrote. Does something not make sense?
              $endgroup$
              – Mike Earnest
              Mar 22 at 0:44










            • $begingroup$
              My mistake. Thanks for the answer. I just reversed things in my head, oops.
              $endgroup$
              – IntegrateThis
              Mar 22 at 0:47
















            1












            $begingroup$


            I have no idea why $q_z=1$ if $ple q$.




            If $p<q$, then this follows simply from the Strong Law of Large Numbers. Let $X_i=+1$ if the hacker wins the $i^th$ block, and $X_i=-1$ if the honest node wins the $i^th$ block. Let $S_n=X_1+X_2+dots+X_n$. The SLLN implies that $S_n/n$ converges to the expected value of $X_i$, which is $q-p>0$. Since $S_n/n$ converges to a positive number, this means $S_n$ gets arbitrarily large, so the hacker will eventually exceed the honest node by any number (including $z$) of blocks.



            When $p=q$, you can instead use the Law of the Iterated logarithm to prove that $S_n$ gets arbitrarily large.




            from what I understand from a binomial distribution, the probability of the attacker catching up from z blocks from behind should be equal to $binomzz q^zp^0=q^z$.




            This is the probability they catch up after exactly $z$ blocks. We want the probability they eventually catch up, after any number of blocks. This is trickier to compute.



            For the probability when $z=1$, see Hitting probability of biased random walk on the integer line. The probability of eventually catching up from a deficit of $z$ is the same as the probability of catching up from a deficit of $1$, a total of $z$ times in a row. This lets you extend the $z=1$ case to general $z$.






            share|cite|improve this answer











            $endgroup$












            • $begingroup$
              Do you not mean let $X_i = -1$ ? Thanks for the answer.
              $endgroup$
              – IntegrateThis
              Mar 22 at 0:35










            • $begingroup$
              @IntegrateThis I meant what I wrote. Does something not make sense?
              $endgroup$
              – Mike Earnest
              Mar 22 at 0:44










            • $begingroup$
              My mistake. Thanks for the answer. I just reversed things in my head, oops.
              $endgroup$
              – IntegrateThis
              Mar 22 at 0:47














            1












            1








            1





            $begingroup$


            I have no idea why $q_z=1$ if $ple q$.




            If $p<q$, then this follows simply from the Strong Law of Large Numbers. Let $X_i=+1$ if the hacker wins the $i^th$ block, and $X_i=-1$ if the honest node wins the $i^th$ block. Let $S_n=X_1+X_2+dots+X_n$. The SLLN implies that $S_n/n$ converges to the expected value of $X_i$, which is $q-p>0$. Since $S_n/n$ converges to a positive number, this means $S_n$ gets arbitrarily large, so the hacker will eventually exceed the honest node by any number (including $z$) of blocks.



            When $p=q$, you can instead use the Law of the Iterated logarithm to prove that $S_n$ gets arbitrarily large.




            from what I understand from a binomial distribution, the probability of the attacker catching up from z blocks from behind should be equal to $binomzz q^zp^0=q^z$.




            This is the probability they catch up after exactly $z$ blocks. We want the probability they eventually catch up, after any number of blocks. This is trickier to compute.



            For the probability when $z=1$, see Hitting probability of biased random walk on the integer line. The probability of eventually catching up from a deficit of $z$ is the same as the probability of catching up from a deficit of $1$, a total of $z$ times in a row. This lets you extend the $z=1$ case to general $z$.






            share|cite|improve this answer











            $endgroup$




            I have no idea why $q_z=1$ if $ple q$.




            If $p<q$, then this follows simply from the Strong Law of Large Numbers. Let $X_i=+1$ if the hacker wins the $i^th$ block, and $X_i=-1$ if the honest node wins the $i^th$ block. Let $S_n=X_1+X_2+dots+X_n$. The SLLN implies that $S_n/n$ converges to the expected value of $X_i$, which is $q-p>0$. Since $S_n/n$ converges to a positive number, this means $S_n$ gets arbitrarily large, so the hacker will eventually exceed the honest node by any number (including $z$) of blocks.



            When $p=q$, you can instead use the Law of the Iterated logarithm to prove that $S_n$ gets arbitrarily large.




            from what I understand from a binomial distribution, the probability of the attacker catching up from z blocks from behind should be equal to $binomzz q^zp^0=q^z$.




            This is the probability they catch up after exactly $z$ blocks. We want the probability they eventually catch up, after any number of blocks. This is trickier to compute.



            For the probability when $z=1$, see Hitting probability of biased random walk on the integer line. The probability of eventually catching up from a deficit of $z$ is the same as the probability of catching up from a deficit of $1$, a total of $z$ times in a row. This lets you extend the $z=1$ case to general $z$.







            share|cite|improve this answer














            share|cite|improve this answer



            share|cite|improve this answer








            edited Mar 22 at 0:30

























            answered Mar 22 at 0:23









            Mike EarnestMike Earnest

            27k22152




            27k22152











            • $begingroup$
              Do you not mean let $X_i = -1$ ? Thanks for the answer.
              $endgroup$
              – IntegrateThis
              Mar 22 at 0:35










            • $begingroup$
              @IntegrateThis I meant what I wrote. Does something not make sense?
              $endgroup$
              – Mike Earnest
              Mar 22 at 0:44










            • $begingroup$
              My mistake. Thanks for the answer. I just reversed things in my head, oops.
              $endgroup$
              – IntegrateThis
              Mar 22 at 0:47

















            • $begingroup$
              Do you not mean let $X_i = -1$ ? Thanks for the answer.
              $endgroup$
              – IntegrateThis
              Mar 22 at 0:35










            • $begingroup$
              @IntegrateThis I meant what I wrote. Does something not make sense?
              $endgroup$
              – Mike Earnest
              Mar 22 at 0:44










            • $begingroup$
              My mistake. Thanks for the answer. I just reversed things in my head, oops.
              $endgroup$
              – IntegrateThis
              Mar 22 at 0:47
















            $begingroup$
            Do you not mean let $X_i = -1$ ? Thanks for the answer.
            $endgroup$
            – IntegrateThis
            Mar 22 at 0:35




            $begingroup$
            Do you not mean let $X_i = -1$ ? Thanks for the answer.
            $endgroup$
            – IntegrateThis
            Mar 22 at 0:35












            $begingroup$
            @IntegrateThis I meant what I wrote. Does something not make sense?
            $endgroup$
            – Mike Earnest
            Mar 22 at 0:44




            $begingroup$
            @IntegrateThis I meant what I wrote. Does something not make sense?
            $endgroup$
            – Mike Earnest
            Mar 22 at 0:44












            $begingroup$
            My mistake. Thanks for the answer. I just reversed things in my head, oops.
            $endgroup$
            – IntegrateThis
            Mar 22 at 0:47





            $begingroup$
            My mistake. Thanks for the answer. I just reversed things in my head, oops.
            $endgroup$
            – IntegrateThis
            Mar 22 at 0:47


















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