\documentclass{article}

\usepackage{../style}

\begin{document}

\fnote{\copyright{} Christian Urban, King's College London, 2014, 2015}

\section*{Handout 6 (Zero-Knowledge Proofs)}

Zero-knowledge proofs (short ZKP) solve a paradoxical puzzle:

How to convince somebody else that one knows a secret, without

revealing what the secret actually is? This sounds like a

problem the Mad Hatter from Alice in Wonderland would occupy

himself with, but actually there some serious and not so

serious applications of it. For example, if you solve

crosswords with your friend, say Bob, you might want to

convince him that you found a solution for one question, but

of course you do not want to reveal the solution, as this

might give Bob an advantage somewhere else in the crossword.

So how to convince Bob that you know the answer (or a secret)?

One way would be to come up with the following protocol:

Suppose the answer is \textit{folio}. Then look up the

definition of \textit{folio} in a dictionary. Say you find:

\begin{quote}

``an \textit{individual} leaf of paper or parchment, either

loose as one of a series or forming part of a bound volume,

which is numbered on the recto or front side only.''

\end{quote}

\noindent

Take the first non-small word\footnote{Let's say the, a, an,

or, and \ldots fall into the category of small words.} in this definition,

in this case \textit{individual}, and look up the definition

of this word, say

\begin{quote}

``a single \textit{human} being as distinct from a group''

\end{quote}

\noindent 

In this definition take the second non-small word, that

is \textit{human}, and again look up the definition of this 

word. This will yield

\begin{quote}

``relating to or \textit{characteristic} of humankind''

\end{quote}

\noindent 

You could go on looking up the definition of the third

non-small word in this definition and so on. But let us assume

you agreed with Bob to stop after three iterations with the

third non-article word in the last definition, that is

\textit{or}. Now, instead of sending to Bob the solution

\textit{folio}, you send to him \textit{characteristic}. 

How can Bob verify that you know the solution? Well, once he

solved it himself, he can use the dictionary and follow the

same ``trail'' as you did. If the final word agrees with what

you had sent him, he must infer you knew the solution earlier

than him. This protocol works like a one-way hash function

because \textit{characteristic} does not give any hint as to

what was the first word was. I leave you to think why this

protocol avoids small words? 

After Bob found his solution and verified that according to

the protocol it ``maps'' also to \textit{characteristic}, can

he be entirely sure no cheating is going on? Not with 100\%

certainty. It could have been possible that he was given

\textit{characteristic} as the word, but it derived from a

different word. This might seem very unlikely, but at least

theoretical it is a possibility. Protocols based on

zero-knowledge proofs will produce a similar result---they

give an answer that might be erroneous in a very small number

of cases. The point is to iterate them long enough so that the

theoretical possibility of cheating is negligibly small. 

By the way, the authors of the paper ``Dismantling Megamos

Crypto: Wirelessly Lockpicking a Vehicle Immobilizer'' who

were barred from publishing their results used also a hash to

prove they did the work and (presumably) managed to get into

cars without a key; see Figure~\ref{paper}. This is very

similar to the method above about crosswords: They like to

prove that they did the work, but not giving out the

``solution''. But this also shows what the problem with such a

method is: yes, we can hide the secret temporarily, but if

somebody else wants to verify it, then the secret has to be

made public. Bob needs to know that \textit{folio} is the

solution before he can verify the claim of Alice that she had

the solution first. Similarly with the car-crypto paper: we

needed to wait until September 2015 when the authors were

finally able to publish their findings in order to verify the

hash. Zero-knowledge proofs, in contrast, can be immediately

checked, even if the secret is not public yet and perhaps

never will be.

\begin{figure}

\begin{center}

\addtolength{\fboxsep}{4mm}

\fbox{\includegraphics[scale=0.4]{../pics/Dismantling_Megamos_Crypto.png}}

\end{center}

\caption{The authors of this paper used a hash in order to prove

later that they have managed to break into cars.\label{paper}}

\end{figure}

\subsubsection*{ZKP: An Illustrative Example}

The idea behind zero-knowledge proofs is not very obvious and

will surely take some time for you to digest. Therefore let us

start with a simple illustrative example. The example will not

be perfect, but hopefully explain the gist of the idea. The

example is called Alibaba's cave, which graphically looks as 

follows:\footnote{The example is taken from an 

article titled ``How to Explain Zero-Knowledge Protocols

to Your Children'' available from 

\url{http://pages.cs.wisc.edu/~mkowalcz/628.pdf}.}

\begin{center}

\begin{tabular}{c@{\hspace{8mm}}c@{\hspace{8mm}}c}

\includegraphics[scale=0.1]{../pics/alibaba1.png} &

\includegraphics[scale=0.1]{../pics/alibaba2.png} &

\includegraphics[scale=0.1]{../pics/alibaba3.png} \\

Step 1 & Step 2 & Step 3

\end{tabular}

\end{center}

\noindent Let us take a closer look at the picture in Step 1:

The cave has a tunnel which forks at some point. Both forks

are connected in a loop. At the deep end of the loop is a

magic wand. The point of the magic wand is that Alice knows

the secret word for how to open it. She wants to keep the word

secret, but wants to convince Bob that she knows it.

One way of course would be to let Bob follow her, but then he

would also find out the secret. So this does not work. To find

a solution, let us first fix the rules: At the beginning Alice

and Bob are outside the cave. Alice goes in alone and takes

either tunnel labelled $A$ in the picture, or the other tunnel

labelled $B$. She waits at the magic wand for the instructions

from Bob, who also goes into the gave and observes what

happens at the fork. He has no knowledge which tunnel Alice

took and calls out (in Step 2) that she should emerge from tunnel

$A$, for example. If she knows the secret for opening the

wand, this will not be a problem for Alice. If she was already

in the $A$-segment of the tunnel, then she just comes back. If

she was in the $B$-segment of the tunnel she will say the magic

word and goes through the wand to emerge from $A$ as requested

by Bob.

Let us have a look at the case where Alice cheats, that is not

knows the secret. She would still go into the cave and use,

for example the $B$-segment of the tunnel. If now Bob says she

should emerge from $B$, she is lucky. But if he says she

should emerge from $A$ then Alice is in trouble: Bob will find

out she does not actually know the secret. So in order to fool

Bob she needs to anticipate his call, and already go into the

corresponding tunnel. This of course also does not work, since

Bob can make any call he wants. Consequently in order to find

out whether Alice cheats, Bob just needs to repeat this

protocol many times. Each time Alice has a chance of

$\frac{1}{2}$ to be lucky or being found out. Iterating this

$n$ times means she must be right every time and when

cheating: the probability for this is $\frac{1}{2}^n$, number

that for already relatively small $n$, say 10, is incredibly 

small.

There are some interesting observations we can make about 

Alibaba's cave and the ZKP protocol between Alice and Bob:

\begin{itemize}

\item {\bf Completeness} If Alice knows the secret, Bob

      accepts Alice ``proof'' for sure. There is no error

      possible in that Bob thinks Alice cheats when she

      actually knows the secret. 

\item {\bf Soundness} If Alice does not know the secret,

      Bob accepts her ``proof'' with a very small probability.

      If, as in the example above, the probability of being

      able to hide cheating is $\frac{1}{2}$ in each round 

      it will be $\frac{1}{2}^n$ after $n$-rounds, which even

      for small $n$ say $> 10$ is very small indeed.

\item {\bf Zero-Knowledge} Even if Bob accepts

      the proof by Alice, he cannot convince anybody else.

\end{itemize} 

\noindent The last property is the most interesting one.

Assume Alice has convinced Bob that she knows the secret and

Bob filmed the whole protocol with a camera. Can he use the

video to convince anybody else? After a moment of thought, you

will agree that this is not the case. Alice and Bob might have

just made it all up and colluded by Bob telling Alice

beforehand which tunnel he will call. In this way it appears

as if all iterations of the protocol were successful, but they

prove nothing. If another person wants to find out whether

Alice knows the secret, he or she would have to conduct the

protocol again. This is actually the formal definition of a

zero-knowledge proof: an independent observer cannot

distinguish between a real protocol (where Alice knows the

secret) and a fake one (where Bob and Alice colluded).

\subsubsection*{Using an Graph-Isomorphism Problem for ZKPs}

Now the question is how can we translate Alibaba's cave into a

computer science solution? It turns out we need an NP problem

for that. The main feature of an NP problem is that it is

computational very hard to generate a solution, but it is very

easy to check whether a given solution indeed solves the

problem at hand.\footnote{The question whether $P = NP$ or not,

we leave to others to speculate about.} 

One NP problem is the \emph{graph isomorphism problem}. It

essentially determines whether the following two graphs, say

$G_1$ and $G_2$, can be moved and stretched so that they look

exactly the same.

\begin{center}

\begin{tabular}{c@{\hspace{8mm}}c@{\hspace{8mm}}c}

$G_1$ & $G_2$\\

\raisebox{-13mm}{\includegraphics[scale=0.4]{../pics/simple.png}} &

\raisebox{-13mm}{\includegraphics[scale=0.4]{../pics/simple-b.png}}&

\footnotesize

\begin{tabular}{rl}

Graph $G_1$	& Graph $G_2$\\

a  & 1\\

b  & 6\\

c  & 8\\

d  & 3\\

g  & 5\\

h  & 2\\

i  & 4\\

j  & 7\\

\end{tabular}

\end{tabular}

\end{center}

\noindent The table on the right gives a mapping of the nodes

of the first graph to the nodes of the second. With this

mapping we can check: node $a$ is connected in $G_1$ with $g$,

$h$ and $i$. Node $a$ maps to node $1$ in $G_2$, which is

connected to $2$, $4$ and $5$, which again correspond via the

mapping to $h$, $i$ and $g$ respectively. Let us write

$\sigma$ for such a table and let us write

\[G_1 = \sigma(G_2)\]

\noindent for two isomorphic graphs ($\sigma$ being the

isomorphism). It is actually very easy to construct two

isomorphic graphs: Start with an arbitrary graph, re-label the

nodes consistently. Alice will need to do this frequently 

for the protocol below. In order to be useful, we therefore

would need to consider substantially larger graphs, like

with thousand nodes. 

Now the secret which Alice tries to hide is the knowledge of

such an isomorphism $\sigma$ between two such graphs. But she

can convince Bob whether she knows such an isomorphism for two

graphs, say $G_1$ and $G_2$, using the same idea as in the

example with Alibaba's cave. For this Alice and Bob must

follow the following protocol:

\begin{enumerate}

\item Alice generates an isomorphic graph $H$ which she sends 

      to Bob (in each iteration she needs to generate a 

      different $H$). 

\item

      After receiving $H$, Bob asks Alice either for an      

      isomorphism between $G_1$ and $H$, or $G_2$ and $H$.

\item Alice and Bob repeat this procedure $n$ times.

\end{enumerate}

\noindent In Step 1 it is important that Alice always 

generates a fresh isomorphic graph. I let you think what

would happen if Alice sends out twice the same graph $H$.

As said before, this is relatively easy to generate by

consistently relabelling nodes. If she started from $G_1$,

Alice will have generated

\begin{equation}

H = \sigma'(G_1)\label{hiso}

\end{equation}

\noindent where $\sigma'$ is the isomorphism between $H$ and

$G_1$. But she could equally have started from $G_2$. In the 

case where $G_1$ and $G_2$ are isomorphic, if $H$ is 

isomorphic with $G_1$, it will also be isomorphic with 

$G_2$, and vice versa. 

After generating $H$, Alice sends it to Bob. The important

point is that she needs to ``commit'' to this $H$, therefore

this kind of zero-knowledge protocols are called

\emph{commitment protocols}. Only after receiving $H$, Bob

will make up his mind about which isomorphism he asks

for---whether between $H$ and $G_1$ or $H$ and $G_2$. For this

he could flip a coin, since the choice should be as

unpredictable for Alice as possible. Once Alice receives the

request, she has to produce an isomorphism. If she generated

$H$ as shown in \eqref{hiso} and is asked for an isomorphism

between $H$ and $G_1$, she just sends $\sigma'$. If she had

been asked for an isomorphism between $H$ and $G_2$, she just

has to compose her secret isomorphism $\sigma$ and $\sigma'$.

The main point for the protocol is that even knowing the

isomorphism between $H$ and $G_1$ or $H$ and $G_2$, will not

make the task easier to find the isomorphism between $G_1$ and

$G_2$, which is the secret Alice tries to protect.

In order to make it crystal clear how this protocol proceeds, 

let us give a version using our more formal notation for 

protocols:

\begin{center}

\begin{tabular}{lrl}

0)  & $A \to B:$ & $G_1$ and $G_2$\\

1a) & $A \to B:$ & $H_1$ \\

1b) & $B \to A:$ & produce isomorphism $G_1 \leftrightarrow H_1$? 

 \quad(or $G_2 \leftrightarrow H_1$)\\

1c) & $A \to B:$ & requested isomorphism\\

2a) & $A \to B:$ & $H_2$\\

2b) & $B \to A:$ & produce isomorphism $G_1 \leftrightarrow H_2$? 

 \quad(or $G_2 \leftrightarrow H_2$)\\

2c) & $A \to B:$ & requested isomorphism\\

    & \ldots\\

\end{tabular}

\end{center}

\noindent As can be seen the protocol runs for some

agreed number of iterations. The $H_i$ Alice needs to 

produce, need to be all distinct. I hope you now know

why?

It is also crucial that in each iteration, Alice first sends

$H_i$ and then Bob can decide which isomorphism he wants:

either $G_1 \leftrightarrow H_i$ or $G_2 \leftrightarrow H_i$.

If somehow Alice can find out before she committed to $H_i$,

she can cheat. For this assume Alice does \emph{not} know an

isomorphism between $G_1$ and $G_2$. If she knows which

isomorphism Bob will ask for she can craft $H$ in such a way

that it is isomorphism with either $G_1$ or $G_2$ (but it

cannot with both). Then in each case she would send Bob

a correct answer and he would come to the conclusion that

all is well. I let you also answer the question whether

such a protocol run between Alice and Bob would convince

a third person, say Pete.

Since the interactive nature of the above PKZ protocol and the

correct ordering of the messages is so important for the

``correctness'' of the protocol, it might look surprising that

the same goal can also me achieved in a completely offline

manner. By this I mean Alice can publish all data at once, and

then at a later time, Bob can inspect the data and come to the

conclusion whether or not Alice knows the secret (again

without actually learning about the secret). For this

Alice has to do the following:

\begin{enumerate}

\item Alice generates $n$ isomorphic graphs

      $H_{1..n}$ (they need to be all distinct)

\item she feeds the $H_{1..n}$ into a hashing function

      (for example encoded as as matrix)

\item she takes the first $n$ bits of the output of the hashing

      function:

      whenever the output is $0$, she shows an isomorphism

      with $G_1$; for $1$ she shows an isomorphism

      with $G_2$

\end{enumerate}

\noindent The reason why this works and achieves the same

goal as the interactive variant is that Alice has no

control over the hashing function. It would be 

computationally just too hard to assemble a set of

$H_{1..n}$ such that she can force where $0$s and $1$s

in the hash values are such that it would pass an external

test. The point is that Alice can publish all this data

on the comfort of her own web-page, for example, and 

in this way convince everybody who bothers to check. 

The virtue of the use of graphs and isomorphism for a 

zero-knowledge protocol is that the idea why it works

are relatively straightforward. The disadvantage is

that encoding any secret into a graph-isomorphism, while

possible, is awkward. The good news is that in fact

any NP problem can be used as part of a ZKP protocol.  

\subsubsection*{Using Modular Logarithms for ZKP Protocols}

While information can be encoded into graph isomorphisms, it

is not the most convenient carrier of information. Clearly it

is much easier to encode information into numbers. Let us look

at zero-knowledge proofs that use numbers as secrets. For this

the underlying NP-problem is to calculate discrete logarithms.

It can be used by choosing public numbers $A$, $B$, $p$, and

private $x$ such that

\begin{center}

$A^x \equiv B\; mod\; p$

\end{center} 

\noindent holds. The secret Alice tries to keep secret is $x$.

The point of the modular logarithm is that it is very hard 

from the public data to calculate $x$ (for large primes). 

Now the protocol proceeds in three stages:

\begin{itemize}

\item {\bf Commitment Stage}

  \begin{enumerate}

    \item Alice generates $z$ random numbers $r_1, \ldots, r_z$, 

      all less than $p - 1$. Alice then sends Bob for all 

      $i = 1,\ldots, z$:

      \[ h_i = A^{r_i}\; mod\; p\]

    \item Bob generates $z$ random bits, say $b_1,\ldots, b_z$. He can do this 

       by flipping $z$ times a coin, for example.

    \item For each bit $b_i$, Alice sends Bob an $s_i$ where

      \begin{center}

      \begin{tabular}{ll}

      if $b_i = 0$: & $s_i = r_i$\\

      if $b_i = 1$: & $s_i = (r_i - r_j) \;mod\; (p -1)$\\

      \end{tabular}

      \end{center}

      where $r_j$ is the lowest $j$ where $b_j = 1$.

    \end{enumerate}

 \end{itemize}   

\noindent For understanding the last step, let $z$ be just 4.

We have four random values $r_i$ chosen by Alice and four

random bits $b_i$ chosen subsequently by Bob, for example

  \begin{center}

  \begin{tabular}{lcccc}

  $r_i$:\; & 4 & 9 & 1 & 3\\ 

  $b_i$:\; & 0 & 1 & 0 & 1\\

  & & $\uparrow$ \\

  & & $j$

  \end{tabular}             

  \end{center}         

  \noindent The highlighted column is the lowest where $b_i = 

  1$ (counted from the left). That means $r_j = 9$. The reason

  for letting Alice choose the random numbers $r_1, \ldots, r_z$

  will become clear shortly. Next is the confirmation 

  phase where Bob essentially checks whether Alice has sent

  him ``correct'' $s_i$ and $h_i$.

\begin{itemize}   

\item {\bf Confirmation Stage}

  \begin{enumerate}

  \item For each $b_i$ Bob checks whether $s_i$ 

  conform to the protocol

  \begin{center}

  \begin{tabular}{ll}

  if $b_i = 0$: & $A^{s_i} \stackrel{?}{\equiv} h_i\;mod\;p$\\

  if $b_i = 1$: & $A^{s_i} \stackrel{?}{\equiv} h_i * h_j^{-1}  \;mod\; p$\\

  \end{tabular}

  \end{center}

  \end{enumerate}

\end{itemize}

\noindent To understand the case for $b_i = 1$, you have 

to do the following calculation: 

\begin{center}

\begin{tabular}{r@{\hspace{1mm}}c@{\hspace{1mm}}l}

$A^{s_i}$ & $=$ & $A^{r_i - r_j}$\\ 

          & $=$ & $A^{r_i} * A^{-r_j}$\\

          & $=$ & $h_{r_i} * h_{r_j}^{-1}\;mod\;p$   

\end{tabular}

\end{center}

\noindent What is interesting that so far nothing has been 

sent about $x$, which is the secret Alice has. Also notice 

that Bob does not know $r_j$. He received 

\begin{center}

$r_j - r_j$,  $r_m - r_j$, \ldots, $r_p - r_j \;mod \;p - 1$ 

\end{center}

\noindent whenever his corresponding bits were $1$. So Bob

does not know $r_j$ and also does not know any $r_i$ where the

bit was $1$. Information about the $x$ is sent in the next

stage (obviously not revealing $x$).

\begin{itemize}   

\item {\bf Proving Stage}

\begin{enumerate}

\item Alice proves she knows $x$, the discrete log of $B$,

by sending