Binomial Random Walks and BitcoinHitting 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
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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
$begingroup$
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.
probability
$endgroup$
add a comment |
$begingroup$
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.
probability
$endgroup$
$begingroup$
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
add a comment |
$begingroup$
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.
probability
$endgroup$
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
probability
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
add a comment |
$begingroup$
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
add a comment |
2 Answers
2
active
oldest
votes
$begingroup$
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).
$endgroup$
add a comment |
$begingroup$
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 $z$.
$endgroup$
$begingroup$
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
add a comment |
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2 Answers
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2 Answers
2
active
oldest
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active
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active
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votes
$begingroup$
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).
$endgroup$
add a comment |
$begingroup$
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).
$endgroup$
add a comment |
$begingroup$
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).
$endgroup$
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).
answered Mar 22 at 0:11
Minus One-TwelfthMinus One-Twelfth
3,233413
3,233413
add a comment |
add a comment |
$begingroup$
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 $z$.
$endgroup$
$begingroup$
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
add a comment |
$begingroup$
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 $z$.
$endgroup$
$begingroup$
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
add a comment |
$begingroup$
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 $z$.
$endgroup$
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 $z$.
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
add a comment |
$begingroup$
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
add a comment |
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Required, but never shown
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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).
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– Minus One-Twelfth
Mar 22 at 0:08
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@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.
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– IntegrateThis
Mar 22 at 0:11