# Introduction

**Additional reading:** Sections 2.1 (Introduction) and 2.2 (Shannon
ciphers and perfect security) in the Boneh Shoup book. Chapters 1 and 2
of Katz-Lindell book.In the current state of these lecture notes, almost all references
and credits are omitted unless the name has become standard in the
literature, or I believe that the story of some discovery can serve
a pedagogical point. See the Katz-Lindell book for historical notes
and references. This lecture shares a lot of text with (though is
not identical to) my lecture on cryptography in the introduction to
theoretical computer science lecture notes.

Ever since people started to communicate, there were some messages that
they wanted kept secret. Thus cryptography has an old though arguably
*undistinguished* history. For a long time cryptography shared similar
features with Alchemy as a domain in which many otherwise smart people
would be drawn into making fatal mistakes.

The definitive text on the history of cryptography is David Kahn’s “The
Codebreakers”, whose title already hints at the ultimate fate of most
cryptosystems.Traditionally, *cryptography* was the name for the activity of
*making* codes, while *cryptoanalysis* is the name for the activity
of *breaking* them, and *cryptology* is the name for the union of
the two. These days *cryptography* is often used as the name for the
broad science of constructing and analyzing the security of not just
encryptions but many schemes and protocols for protecting the
confidentiality and integrity of communication and computation. (See also “The Code Book” by Simon Singh.) We now
recount just a few stories to get a feel for this field. But, before we
do so, we should introduce the cast of characters. The basic setting of
“encryption” or “secret writing” is the following: one person, whom we
will call **Alice**, wishes to send another person, whom we will call
**Bob**, a **secret** message. Since Alice and Bob are not in the same
room (perhaps because Alice is imprisoned in a castle by her cousin the
queen of England), they cannot communicate directly and need to send
their message in writing. Alas, there is a third person, whom we will
call **Eve**, that can see their message. Therefore Alice needs to find
a way to *encode* or *encrypt* the message so that only Bob (and not
Eve) will be able to understand it.

In 1587, Mary the queen of Scots, and the heir to the throne of England,
wanted to arrange the assasination of her cousin, queen Elisabeth I of
England, so that she could ascend to the throne and finally escape the
house arrest under which she has been for the last 18 years. As part of
this complicated plot, she sent a coded letter to Sir Anthony Babington.
It is what’s known as a *substitution cipher* where each letter is
transformed into a different symbol, and so the resulting letter looks
something like the following (see Reference:figmaryletter):

At a first look, such a letter might seem rather inscrutable- a
meaningless sequence of strange symbols. However, after some thought,
one might recognize that these symbols *repeat* several times and
moreover that different symbols repeat with different frequencies. Now
it doesn’t take a large leap of faith to assume that perhaps each symbol
corresponds to a different letter and the more frequent symbols
correspond to letters that occur in the alphabet with higher frequency.
From this observation, there is a short gap to completely breaking the
cipher, which was in fact done by queen Elisabeth’s spies who used the
decoded letters to learn of all the co-conspirators and to convict queen
Mary of treason, a crime for which she was executed.

Trusting in superficial security measures (such as using “inscrutable” symbols) is a trap that users of cryptography have been falling into again and again over the years. As in many things, this is the subject of a great XKCD cartoon (see Reference:xkcdnavajofig):

The Vigenère cipher is named after Blaise de Vigenère who described it in a book in 1586 (though it was invented earlier by Bellaso). The idea is to use a collection of subsitution cyphers - if there are \(n\) different ciphers then the first letter of the plaintext is encoded with the first cipher, the second with the second cipher, the \(n^{th}\) with the \(n^{th}\) cipher, and then the \(n+1^{st}\) letter is again encoded with the first cipher. The key is usually a word or a phrase of \(n\) letters, and the \(i^{th}\) substition cipher is obtained by shifting each letter \(k_i\) positions in the alphabet. This “flattens” the frequencies and makes it much harder to do frequency analysis, which is why this cipher was considered “unbreakable” for 300+ years and got the nickname “le chiffre indéchiffrable” (“the unbreakable cipher”). Nevertheless, Charles Babbage cracked the Vigenère cipher in 1854 (though he did not publish it). In 1863 Friedrich Kasiski broke the cipher and published the result. The idea is that once you guess the length of the cipher, you can reduce the task to breaking a simple substitution cipher which can be done via frequency analysis (can you see why?). Confederate generals used Vigenère regularly during the civil war, and their messages were routinely cryptanalzed by Union officers.

The story of the *Enigma* cipher had been told many times (see for
example Kahn’s book as well as Andrew Hodges’ biography of Alan Turing).
This was a mechanical cipher (looking like a typewriter) where each
letter typed would get mapped into a different letter depending on the
(rather complicated) key and current state of the machine which had
several rotors that rotated at different paces. An identically wired
machine at the other end could be used to decrypt. Just as many ciphers
in history, this has also been believed by the Germans to be “impossible
to break” and even quite late in the war they refused to believe it was
broken despite mounting evidence to that effect. (In fact, some German
generals refused to believe it was broken even *after* the war.)
Breaking Enigma was an heroic effort which was initiated by the Poles
and then completed by the British at Bletchley Park; as part of this
effort they built arguably the world’s first large scale mechanical
computation devices (though they looked more similar to washing machines
than to iPhones). They were also helped along the way by some quirks and
errors of the german operators. For example, the fact that their
messages ended with “Heil Hitler” turned out to be quite useful. Here is
one entertaining anecdote: the Enigma machine would never map a letter
to itself. In March 1941, Mavis Batey, a cryptanalyst at Bletchley Park
received a very long message that she tried to decrypt. She then noticed
a curious property— the message did *not* contain the letter “L.”Here is a nice exercise: compute (up to an order of magnitude) the
probability that a 50-letter long message composed of random letters
will end up not containing the letter “L”.
She realized that for such a long message not contain “L” could not
happen by chance, and hence surmised that the original message probably
composed *only* of L’s. That is, it must have been the case that the
operator, perhaps to test the machine, have simply sent out a message
where he repeatedly pressed the letter “L”. This observation helped her
decode the next message, which helped inform of a planned Italian attack
and secure a resounding British victory in what became known as “the
Battle of Cape Matapan”. Mavis also helped break another Enigma machine
which helped in the effort of feeding the Germans with the false
information that the main allied invasion would take place in Pas de
Calais rather than on Normandy. See this inteview with Sir Harry
Hinsley for more on the
effect of breaking the Enigma on the war. General Eisenhower said that
the intelligence from Bletchley park was of “priceless value” and made a
“very decisive contribution to the Allied war effort”.

## Defining encryptions

Many of the troubles that cryptosystem designers faced over history (and
still face!) can be attributed to not properly defining or understanding
what are the goals they want to achieve in the first place. We now turn
to actually defining what is an encryption scheme. Clearly we can encode
every message as a string of bits, i.e., an element of \(\{0,1\}^\ell\)
for some \(\ell\). Similarly, we can encode the *key* as a string of bits
as well, i.e., an element of \(\{0,1\}^n\) for some \(n\). Thus, we can
think of an encryption scheme as composed of two functions. The
*encryption function* \(E\) maps a secret key \(k \in \{0,1\}^n\) and a
message (known also as *plaintext*) \(m\in \{0,1\}^\ell\) into a
*ciphertext* \(c \in \{0,1\}^L\) for some \(L\). We write this as
\(c = E_k(m)\). The *decryption function* \(D\) does the reverse operation,
mapping the secret key \(k\) and the cyphertext \(c\) back into the
plaintext message \(m\), which we write as \(m = D_k(c)\). The basic
equation is that if we use the same key for encryption and decryption,
then we should get the same message back. That is, for every
\(k \in \{0,1\}^n\) and \(m\in \{0,1\}^\ell\), \[ m = D_k(E_k(m)) \;.\]

Formally, we make the following definition:

A pair of functions \((E,D)\) mapping strings to strings is a *valid
private key encryption scheme* (or *encryption scheme* for short) if
there are some numbers \(n,\ell,L\) such that
\(E:\{0,1\}^n \times \{0,1\}^\ell \rightarrow \{0,1\}^L\) and
\(D:\{0,1\}^n \times \{0,1\}^L \rightarrow \{0,1\}^\ell\) and for every
for every \(k\in \{0,1\}^n\) and \(x \in \{0,1\}^{\ell}\), \[
D(k,E(k,x))=x \;. \label{eqvalidenc}
\] We will typically write the first input (i.e., the key) to the
encryption and decryption functions as a subscribt, and so write
\eqref{eqvalidenc} as \(D_k(E_k(x))=x\).

A note on notation:We will always use \(i,j,\ell,n\) to denote natural numbers. \(n\) will often denote the length of our secret key, and \(\ell\) the length of the message, sometimes also known as “block length” since longer messages are simply chopped into “blocks” of length \(\ell\) and also appropriately padded. We will use \(k\) to denote the secret key, \(m\) to denote the secret plaintext message, and \(c\) to denote the encrypted ciphertext. Note that \(c,m\) and \(k\) are bit strings of lengths \(o,\ell\) and \(n\) respectively. The length of the secret key is often known as the “security parameter” and in other texts it is often denoted by \(k\) or \(\kappa\). We use \(n\) to correspond with the standard algorithmic notation for input length (as in \(O(n)\) time algorithms).

Reference:encryptiondef says nothing about security and does not rule
out trivial “encryption” schemes such as the scheme \(E_k(m) = m\) that
simply outputs the plaintext as is. Defining security is tricky, and
we’ll take it one step at a time, but lets start by pondering what is
secret and what is not. A priori we are thinking of an attacker Eve that
simply sees the ciphertext \(y=E_k(x)\) and does not know anything on how
it was generated. So, it does not know the details of \(E\) and \(D\), and
certainly does not know the secret key \(k\). However, many of the
troubles past cryptosystems went through was caused by them relying on
“security through obscurity”— trusting that the fact their *methods*
are not known to their enemy will protect them from being broken. This
is a faulty assumption - if you reuse a method again and again (even
with a different key each time) then eventually your adversaries will
figure out what you are doing. And if Alice and Bob meet frequently in a
secure location to decide on a new method, they might as well take the
opportunity to exchange their secrets.. These considerations led
Kerchoffs to state the following principle:

A cryptosystem should be secure even if everything about the system, except the key, is public knowledge.(Auguste Kerckhoffs, 1883)

(The actual quote is “Il faut qu’il n’exige pas le secret, et qu’il puisse sans inconvénient tomber entre les mains de l’ennemi” loosely translated as “The system must not require secrecy and can be stolen by the enemy without causing trouble”. According to Steve Bellovin the NSA version is “assume that the first copy of any device we make is shipped to the Kremlin”.)

Why is it OK to assume the key is secret and not the algorithm? Because
we can always choose a fresh key. But of course if we choose our key to
be “1234” or “passw0rd!” then that is not exactly secure. In fact, if
you use any deterministic algorithm to choose the key then eventually
your adversary will figure out. Therefore for security we must choose
the key at *random*. Thus following can be thought of as a restatement
of Kerchkoffs’s principle:

There is no secrecy without randomness

This is such a crucial point that is worth repeating:

There is no secrecy without randomness

At the heart of every cryptographic scheme there is a secret key, and the secret key is always chosen at random. A corollary of that is that to understand cryptography, you need to know some probability theory. Fortunately, we don’t need much of probability- only probability over finite spaces, and basic notions such as expectation, variance, concentration and the union bound suffice for most of we need. In fact, understanding the following two statements will already get you much of what you need for cryptography:

- For every fixed string \(x\in\{0,1\}^n\), if you toss a coin \(n\) times, the probability that the heads/tails pattern will be exactly \(x\) is \(2^{-n}\).
- A probability of \(2^{-128}\) is really really small.

### Generating randomness in actual cryptographic systems

How do we actually get random bits in actual systems? The main idea is
to use a two stage approach. First we need to get some data that is
*unpredictable* from the point of view of an attacker on our system.
Some sources for this could be measuring latency on the network or hard
drives (getting harder with solid state disk), user keyboard and mouse
movement patterns (problematic when you need fresh randomness at boot
time ), clock drift and more, there are some other sources including
audio, video, and network. All of these can be problematic, especially
for servers or virtual machines, and so hardware based random number
generators based on phenomena such as thermal noise or nuclear decay are
becoming more popular. Once we have some data \(X\) that is unpredictable,
we need to estimate the *entropy* in it. You can roughly imagine that
\(X\) has \(k\) bits of entropy if the probability that an attacker can
guess \(X\) is at most \(2^{-k}\). People then use a *hash function* (an
object we’ll talk about more later) to map \(X\) into a string of length
\(k\) which is then hopefully distributed (close to) uniformly at random.
All of this process, and especially understanding the amount of
information an attacker may have on the entropy sources, is a bit of a
dark art and indeed a number of attacks on cryptographic systems were
actually enabled by weak generation of randomness. Here are a few
examples.

One of the first attacks was on the SSL implementation of Netscape
(*the* browser at the time). Netscape use the following “unpredicatable”
information— the time of day and a process ID both of which turned out
to be quite predictable (who knew attackers have clocks too?). Netscape
tried to protect its security through “security through obscurity” by
not releasing the source code for their pseudorandom generator, but it
was reverse engineered by Ian Goldberg and David
Wagner (Ph.D
students at the time) who demonstrated this attack.

In 2006 a programmer removed a line of code from the procedure to generate entropy in OpenSSL package distributed by Debian since it caused a warning in some automatic verification code. As a result for two years (until this was discovered) all the randomness generated by this procedure used only the process ID as an “unpredictable” source. This means that all communication done by users in that period is fairly easily breakable (and in particular, if some entities recorded that communication they could break it also retroactively). This caused a huge headache and a worldwide regeneration of keys, though it is believed that many of the weak keys are still used. See XKCD’s take on that incident.

In 2012 two separate teams of researchers scanned a large number of RSA keys on the web and found out that about 4 percent of them are easy to break. The main issue were devices such as routers, internet-connected printers and such. These devices sometimes run variants of Linux- a desktop operating system- but without a hard drive, mouse or keyboard, they don’t have access to many of the entropy sources that desktop have. Coupled with some good old fashioned ignorance of cryptography and software bugs, this led to many keys that are downright trivial to break, see this blog post and this web page for more details.

After the entropy is collected and then “purified” or “extracted” to a
uniformly random string that is, say, a few hundred bits long, we often
need to “expand” it into a longer string that is also uniform (or at
least looks like that for all practical purposes). We will discuss how
to go about that in the next lecture. This step has its weaknesses too
and in particular the Snowden documents, combined with observations of
Shumow and Ferguson, strongly suggest that the NSA has deliberately
inserted a *trapdoor* in one of the pseudorandom generators published by
the National Institute of Standards and Technologies (NIST).
Fortunately, this generator wasn’t widely adapted but apparently the NSA
did pay 10 million dollars to RSA security so the latter would make this
generator their default option in their products.

## Defining the secrecy requirement.

Defining the secrecy requirement for an encryption is not simple. Over the course of history, many smart people got it wrong and convinced themselves that ciphers were impossible to break. The first person to truly ask the question in a rigorous way was Claude Shannon in 1945 (though a partial version of his manuscript was only declassified in 1949). Simply by asking this question, he made an enormous contribution to the science of cryptography and practical security. We now will try to examine how one might answer it.

Let me warn you ahead of time that we are going to insist on a
*mathematically precise definition* of security. That means that the
definition must capture security in all cases, and the existence of a
single counterexample, no matter how “silly”, would make us rule out a
candidate definition. This exercise of coming up with “silly”
counterexamples might seem, well, silly. But in fact it is this method
that has led Shannon to formulate his theory of secrecy, which (after
much followup work) eventually revolutionized cryptography, and brought
this science to a new age where Edgar Allan Poe’s maxim no longer holds,
and we are able to design ciphers which human (or even nonhuman)
ingenuity cannot break.

The most natural way to attack an encryption is for Eve to guess all possible keys. In many encryption schemes this number is enormous and this attack is completely infeasible. For example, the theoretical number of possibilities in the Enigma cipher was about \(10^{113}\) which roughly means that even if we built a filled the milky way galaxy with computers operating at light speed, the sun would still die out before it finished examining all the possibilities.There are about \(10^{68}\) atoms in the galaxy, so even if we assumed that each one of those atoms was a computer that can process say \(10^{21}\) decryption attempts per second (as the speed of light is \(10^9\) meters per second and the diamter of an atom is about \(10^{-12}\) meters), then it would still take \(10^{113-89} = 10^{24}\) seconds, which is about \(10^{17}\) years to exhaust all possibilities, while the sun is estimated to burn out in about 5 billion years. One can understand why the Germans thought it was impossible to break. (Note that despite the number of possibilities being so enormous, such a key can still be easily specified and shared between Alice and Bob by writing down \(113\) digits on a piece of paper.) Ray Miller of the NSA had calculated that, in the way the Germans used the machine, the number of possibilities was “only” \(10^{23}\), but this is still extremely difficult to pull off even today, and many orders of magnitudes above the computational powers during the WW-II era. Thus clearly, it is sometimes possible to break an encryption without trying all possibilities. A corollary is that having a huge number of key combinations does not guarantee security, as an attacker might find a shortcut (as the allies did for Enigma) and recover the key without trying all options.

Since it is possible to recover the key with some tiny probability (e.g. by guessing it at random), perhaps one way to define security of an encryption scheme is that an attacker can never recover the key with probability significantly higher than that. Here is an attempt at such a definition:

An encyption scheme \((E,D)\) is *\(n\)-secure* if no matter what method Eve
employs, the probability that she can recover the true key \(k\) from the
ciphertext \(c\) is at most \(2^{-n}\).

When you see a mathematical definition that attempts to model some real-life phenomenon such as security, you should pause and ask yourself:

- Do I understand mathematically what is the definition stating?
- Is it a reasonable way to capture the real life phenomenon we are discussing?

One way to answer question 2 is to try to think of both examples of objects that satisfy the definition and examples of objects that violate it, and see if this conforms to your intuition about whether these objects display the phenomenon we are trying to capture. Try to do this for Reference:securefirstattemptdef

You might wonder if Reference:securefirstattemptdef is not *too strong*.
After all how are we going ever to prove that Eve cannot recover the
secret key no matter what she does? Edgar Allan Poe would say that there
can always be a method that we overlooked. However, in fact this
definition is too *weak*! Consider the following encryption: the secret
key \(k\) is chosen at random in \(\{0,1\}^n\) but our encryption scheme
simply ignores it and lets \(E_k(x)=x\) and \(D_k(y)=y\). This is a valid
encryption, but of course completely insecure as we are simply
outputting the plaintext in the clear. Yet, no matter what Eve does, if
she only sees \(c\) and not \(k\), there is no way she can guess the true
value of \(k\) with probability better than \(2^{-n}\), since it was chosen
completely at random and she gets no information about it. Formally, one
can prove the following result:

Let \((E,D)\) be the encryption scheme above. For every function \(Eve:\{0,1\}^\ell\rightarrow \{0,1\}^n\) and for every \(x\in \{0,1\}^\ell\), the probability that \(Eve(E_k(x))=k\) is exactly \(2^{-n}\).

This follows because \(E_k(x)=x\) and hence \(Eve(E_k(x))=Eve(x)\) which is some fixed value \(k'\in\{0,1\}^n\) that is independent of \(k\). Hence the probability that \(k=k'\) is \(2^{-n}\). QED

The math behind the above argument is very simple, yet I urge you to read and re-read the last two paragraphs until you are sure that you completely understand why this encryption is in fact secure according to the above definition. This is a “toy example” of the kind of reasoning that we will be employing constantly throughout this course, and you want to make sure that you follow it.

So, Reference:trivialsec is true, but one might question its meaning.
Clearly this silly example was not what we meant when stating this
definition. However, as mentioned above, we are not willing to ignore
even silly examples and must amend the definition to rule them out. One
obvious objection is that we don’t care about hiding the key- it is the
*message* that we are trying to keep secret. This suggests the next
attempt:

An encryption scheme \((E,D)\) is *\(n\)-secure* if for every message \(x\) no
matter what method Eve employs, the probability that she can recover \(x\)
from the ciphertext \(y=E_k(x)\) is at most \(2^{-n}\).

Now this seems like it captures our intended meaning. But remember that
we are being anal, and truly insist that the definition holds as stated,
namely that for every plaintext message \(x\) and every function
\(Eve:\{0,1\}^L\rightarrow\{0,1\}^\ell\), the probability over the choice
of \(k\) that \(Eve(E_k(x))=x\) is at most \(2^{-n}\). But now we see that
this is clearly impossible. After all, this is supposed to work for
*every* message \(x\) and *every* function \(Eve\), but clearly if \(x\) is
the all-zeroes message \(0^\ell\) and \(Eve\) is the function that ignores
its input and simply outputs \(0^\ell\), then it will hold that
\(Eve(E_k(x))=x\) with probability one.

So, if before the definition was too weak, the new definition is too
strong and is impossible to achieve. The problem is that of course we
could guess a fixed message with probability one, so perhaps we could
try to consider a definition with a *random* message. That is:

An encyption scheme \((E,D)\) is *\(n\)-secure* if no matter what method Eve
employs, if \(x\) is chosen at random from \(\{0,1\}^\ell\), the probability
that she can recover \(x\) from the ciphertext \(c=E_k(x)\) is at most
\(2^{-n}\).

This weakened definition can in fact be achieved, but we have again weakened it too much. Consider an encryption that hides the last \(\ell/2\) bits of the message, but completely reveals the first \(\ell/2\) bits. The probability of guessing a random message is \(2^{-\ell/2}\), and so such a scheme would be “\(\ell/2\) secure” per Reference:securethirdattemptdef but this is still a scheme that you would not want to use. The point is that in practice we don’t encrypt random messages— our messages might be in English, might have common headers, and might have even more structures based on the context. In fact, it may be that the message is either “Yes” or “No” (or perhaps either “Attack today” or “Attack tomorrow”) but we want to make sure Eve doesn’t learn which one it is. So, using an encryption scheme that reveals the first half of the message (or frankly even only the first bit) is unacceptable.

## Perfect Secrecy

So far all of our attempts at definitions oscillated between being too
strong (and hence impossible) or too weak (and hence not guaranteeing
actual security). The key insight of Shannon was that in a secure
encryption scheme the ciphtertext should not reveal *any additional
information* about the plaintext. So, if for example it was a priori
possible for Eve to guess the plaintext with some probability \(1/k\)
(e.g., because there were only \(k\) possiblities for it) then she should
not be able to guess it with higher probability after seeing the
ciphertext. This can be formalized as follows:

An encryption scheme \((E,D)\) is *perfectly secret* if there for every
set \(M\subseteq\{0,1\}^\ell\) of plaintexts, and for every strategy used
by Eve, if we choose at random \(x\in M\) and a random key
\(k\in\{0,1\}^n\), then the probability that Eve guesses \(x\) after seeing
\(E_k(x)\) is at most \(1/|M|\).

In particular, if we encrypt either “Yes” or “No” with probability \(1/2\), then Eve won’t be able to guess which one it is with probability better than half. In fact, that turns out to be the heart of the matter:

An encryption scheme \((E,D)\) is perfectly secret if and only if for every two distinct plaintexts \(\{x_0,x_1\} \subseteq \{0,1\}^\ell\) and every strategy used by Eve, if we choose at random \(b\in\{0,1\}\) and a random key \(k\in\{0,1\}^n\), then the probability that Eve guesses \(x_b\) after seeing \(E_k(x_b)\) is at most \(1/2\).

The “only if” direction is obvious— this condition is a special case of the perfect secrecy condition for a set \(M\) of size \(2\).

The “if” direction is trickier. We need to show that if there is some set \(M\) (of size possibly much larger than \(2\)) and some strategy for Eve to guess (based on the ciphertext) a plaintext chosen from \(M\) with probability larger than \(1/|M|\), then there is also some set \(M'\) of size two and a strategy \(Eve'\) for Eve to guess a plaintext chosen from \(M'\) with probability larger than \(1/2\).

Let’s fix the message \(x_0\) to be the all zeroes message and pick \(x_1\) at random in \(M\). Under our assumption, it holds that for random key \(k\) and message \(x_1\in M\), \[\Pr_{k \leftarrow \{0,1\}^n, x_1 \leftarrow M}[Eve(E_k(x_1))=x_1] > 1/|M|\;.\] On the other hand, for every choice of \(k\), \(x'= Eve(E_k(x_0))\) is a fixed string independent on the choice of \(x_1\), and so if we pick \(x_1\) at random in \(M\), then the probability that \(x_1=x'\) is at most \(1/|M|\), or in other words \[\Pr_{k \leftarrow \{0,1\}^n, x_1 \leftarrow M}[Eve(E_k(x_0))=x_1] \leq 1/|M|\;.\]

Thus in particular, due to linearity of expectation, there *exists* some
\(x_1\) satisfying
\[ \Pr[Eve(E_k(x_1))=x_1] > \Pr[Eve(E_k(x_0))=x_1] \;.\] (Can you see
why? This is worthwhile stopping and reading again.) But this can be
turned into an attacker \(Eve'\) such that for \(b \leftarrow_R \{0,1\}\).
the probability that \(Eve'(E_k(x_b))=x_b\) is larger than \(1/2\). Indeed,
we can define \(Eve'(y)\) to output \(x_1\) if \(Eve(y)=x_1\) and otherwise
output a random message in \(\{ x_0 , x_1 \}\). The probability that
\(Eve'(y)\) equals \(x_1\) is higher when \(y=E_k(x_1)\) than when
\(y=E_k(x_0)\), and since \(Eve'\) outputs either \(x_0\) or \(x_1\), this means
that the probability that \(Eve'(E_k(x_b))=x_b\) is larger than \(1/2\).
(Can you see why?)

The proof of Reference:twotomanythm is not trivial, and is worth reading again and making sure you understand it. An excellent exercise, which I urge you to pause and do now is to prove the following: \((E,D)\) is perfectly secret if for every plaintexts \(x,x' \in \{0,1\}^\ell\), the two random variables \(\{ E_k(x) \}\) and \(\{ E_{k'}(x') \}\) (for randomly chosen keys \(k\) and \(k'\)) have precisely the same distribution.

So, perfect secrecy is a natural condition, and does not seem to be too weak for applications, but can it actually be achieved? After all, the condition that two different plaintexts are mapped to the same distribution seems somewhat at odds with the condition that Bob would succeed in decrypting the ciphertexts and find out if the plaintext was in fact \(x\) or \(x'\). It turns out the answer is yes! For example, Reference:onetimepadtwofig details a perfectly secret encryption for two bits.

In fact, this can be generalized to any number of bits:

There is a perfectly secret valid encryption scheme \((E,D)\) with \(L(n)=n\).

Our scheme is the one-time pad also known as the “Vernam Cipher”, see Reference:onetimepadfig. The encryption is exceedingly simple: to encrypt a message \(x\in \{0,1\}^n\) with a key \(k \in \{0,1\}^n\) we simply output \(x \oplus k\) where \(\oplus\) is the bitwise XOR operation that outputs the string corresponding to XORing each coordinate of \(x\) and \(k\).

For two binary strings \(a\) and \(b\) of the same length \(n\), we define \(a \oplus b\) to be the string \(c \in \{0,1\}^n\) such that \(c_i = a_i + b_i \mod 2\) for every \(i\in [n]\). The encryption scheme \((E,D)\) is defined as follows: \(E_k(x) = x\oplus k\) and \(D_k(y)= y \oplus k\). By the associative law of addition (which works also modulo two), \(D_k(E_k(x))=(x\oplus k) \oplus k = x \oplus (k \oplus k) = x \oplus 0^n = x\), using the fact that for every bit \(\sigma \in \{0,1\}\), \(\sigma + \sigma \mod 2 = 0\) and \(\sigma + 0 = \sigma \mod 2\). Hence \((E,D)\) form a valid encryption.

To analyze the perfect secrecy property, we claim that for every \(x\in \{0,1\}^n\), the distribution \(Y_x=E_k(x)\) where \(k \sim \{0,1\}^n\) is simply the uniform distribution over \(\{0,1\}^n\), and hence in particular the distributions \(Y_{x}\) and \(Y_{x'}\) are identical for every \(x,x' \in \{0,1\}^n\). Indeed, for every particular \(y\in \{0,1\}^n\), the value \(y\) is output by \(Y_x\) if and only if \(y = x \oplus k\) which holds if and only if \(k= x \oplus y\). Since \(k\) is chosen uniformly at random in \(\{0,1\}^n\), the probability that \(k\) happens to equal \(k \oplus y\) is exactly \(2^{-n}\), which means that every string \(y\) is output by \(Y_x\) with probability \(2^{-n}\).

The argument above is quite simple but is worth reading again. To
understand why the one-time pad is perfectly secret, it is useful to
envision it as a bipartite graph as we’ve done in
Reference:onetimepadtwofig. (In fact the encryption scheme of
Reference:onetimepadtwofig is precisely the one-time pad for \(n=2\).) For
every \(n\), the one-time pad encryption scheme corresponds to a bipartite
graph with \(2^n\) vertices on the “left side” corresponding to the
plaintexts in \(\{0,1\}^n\) and \(2^n\) vertices on the “right side”
corresponding to the ciphertexts \(\{0,1\}^n\). For every \(x\in \{0,1\}^n\)
and \(k\in \{0,1\}^n\), we connect \(x\) to the vertex \(y=E_k(x)\) with an
edge that we label with \(k\). One can see that this is the complete
bipartite graph, where every vertex on the left is connected to *all*
vertices on the right. In particular this means that for every left
vertex \(x\), the distribution on the ciphertexts obtained by taking a
random \(k\in \{0,1\}^n\) and going to the neighbor of \(x\) on the edge
labeled \(k\) is the uniform distribution over \(\{0,1\}^n\). This ensures
the perfect secrecy condition.

## Necessity of long keys

So, does Reference:onetimepad give the final word on cryptography, and means that we can all communicate with perfect secrecy and live happily ever after? No it doesn’t. While the one-time pad is efficient, and gives perfect secrecy, it has one glaring disadvantage: to communicate \(n\) bits you need to store a key of length \(n\). In contrast, practically used cryptosystems such as AES-128 have a short key of \(128\) bits (i.e., \(16\) bytes) that can be used to protect terabytes or more of communication! Imagine that we all needed to use the one time pad. If that was the case, then if you had to communicate with \(m\) people, you would have to maintain (securely!) \(m\) huge files that are each as long as the length of the maximum total communication you expect with that person. Imagine that every time you opened an account with Amazon, Google, or any other service, they would need to send you in the mail (ideally with a secure courier) a DVD full of random numbers, and every time you suspected a virus, you’d need to ask all these services for a fresh DVD. This doesn’t sound so appealing.

This is not just a theoretical issue. The Soviets have used the one-time pad for their confidential communication since before the 1940’s. In fact, even before Shannon’s work, the U.S. intelligence already knew in 1941 that the one-time pad is in principle “unbreakable” (see page 32 in the Venona document). However, it turned out that the hassle of manufacturing so many keys for all the communication took its toll on the Soviets and they ended up reusing the same keys for more than one message. They did try to use them for completely different receivers in the (false) hope that this wouldn’t be detected. The Venona Project of the U.S. Army was founded in February 1943 by Gene Grabeel (see Reference:genegrabeelfig), a former home economics teacher from Madison Heights, Virgnia and Lt. Leonard Zubko. In October 1943, they had their breakthrough when it was discovered that the Russians were reusing their keys.Credit to this discovery is shared by Lt. Richard Hallock, Carrie Berry, Frank Lewis, and Lt. Karl Elmquist, and there are others that have made important contribution to this project. See pages 27 and 28 in the document. In the 37 years of its existence, the project has resulted in a treasure chest of intelligence, exposing hundreds of KGB agents and Russian spies in the U.S. and other countries, including Julius Rosenberg, Harry Gold, Klaus Fuchs, Alger Hiss, Harry Dexter White and many others.

Unfortunately it turns out that (as shown by Shannon) that such long
keys are *necessary* for perfect secrecy:

For every perfectly secret encryption scheme \((E,D)\) the length function \(L\) satisfies \(L(n) \leq n\).

The idea behind the proof is illustrated in Reference:longkeygraphfig. If the number of keys is smaller than the number of messages then the neighborhoods of all vertices in the corresponding graphs cannot be identical.

Let \(E,D\) be a valid encryption scheme with messages of length \(L\) and key of length \(n<L\). We will show that \((E,D)\) is not perfectly secret by providing two plaintexts \(x_0,x_1 \in \{0,1\}^L\) such that the distributions \(Y_{x_0}\) and \(Y_{x_1}\) are not identical, where \(Y_x\) is the distribution obtained by picking \(k \sim \{0,1\}^n\) and outputting \(E_k(x)\). We choose \(x_0 = 0^L\). Let \(S_0 \subseteq \{0,1\}^*\) be the set of all ciphertexts that have nonzero probability of being output in \(Y_{x_0}\). That is, \(S=\{ y \;|\; \exists_{k\in \{0,1\}^n} y=E_k(x_0) \}\). Since there are only \(2^n\) keys, we know that \(|S_0| \leq 2^n\).

We will show the following claim:

**Claim I:** There exists some \(x_1 \in \{0,1\}^L\) and \(k\in \{0,1\}^n\)
such that \(E_k(x_1) \not\in S_0\).

Claim I implies that the string \(E_k(x_1)\) has positive probability of
being output by \(Y_{x_1}\) and zero probability of being output by
\(Y_{x_0}\) and hence in particular \(Y_{x_0}\) and \(Y_{x_1}\) are not
identical. To prove Claim I, just choose a fixed \(k\in \{0,1\}^n\). By
the validity condition, the map \(x \mapsto E_k(x)\) is a one to one map
of \(\{0,1\}^L\) to \(\{0,1\}^*\) and hence in particular the *image* of
this map: the set \(I = \{ y \;|\; \exists_{x\in \{0,1\}^L} y=E_k(x) \}\)
has size at least (in fact exactly) \(2^L\). Since \(|S_0| = 2^n < 2^L\),
this means that \(|I|>|S_0|\) and so in particular there exists some
string \(y\) in \(I \setminus S_0\). But by the definition of \(I\) this means
that there is some \(x\in \{0,1\}^L\) such that \(E_k(x) \not\in S_0\) which
concludes the proof of Claim I and hence of Reference:longkeysthm.

### Advanced comment: Adding probability into the picture

There is a sense in which both our secrecy and our impossiblity results
might not be fully convincing, and that is that we did not explicitly
consider algorithms that use *randomness* . For example, maybe Eve can
break a perfectly secret encryption if she is not modeled as a
deterministic function \(Eve:\{0,1\}^o\rightarrow\{0,1\}^\ell\) but rather
a *probabilistic* process. Similarly, maybe the encryption and
decryption functions could be probabilistic processes as well. It turns
out that none of those matter. For the former, note that a probabilistic
process can be thought of as a *distribution* over functions, in the
sense that we have a collection of functions \(f_1,...,f_N\) mapping
\(\{0,1\}^o\) to \(\{0,1\}^\ell\), and some probabilities \(p_1,\ldots,p_N\)
(non-negative numbers summing to \(1\)), so we now think of Eve as
selecting the function \(f_i\) with probability \(p_i\). But if none of
those functions can give an advantage better than \(1/2\), then neither
can this collection. A similar (though more involved) argument shows
that the impossiblity result showing that the key must be at least as
long as the message still holds even if the encryption and decryption
algorithms are allowed to be probabilistic processes as well (working
this out is a great exercise).