As quantum computers become more and more powerful, they have the potential to completely
reshape the cybersecurity landscape.
So in this video, we're going to talk about what it means to become quantum safe and talk
about terms like quantum safe cryptography.
But before we dive into that, let's first take some time to do a quick recap on classical
cryptography.
Most of our modern encryption protocols are based on a combination of symmetric and asymmetric
encryption.
So let's start by talking about symmetric encryption.
We're going to use a classic example of Alice, who wants to send a secure message to her
friend, Bob.
In order to do this, she first needs to encrypt her message, which she can do using a secret
key.
She can then securely send her message to Bob, who can then decrypt that message using
the same secret key.
And asymmetric encryption works in a very similar way.
But instead of Alice and Bob using the same secret key, Alice will have a public key and
Bob will have a private key.
So these keys are different.
One is mathematically derived from the other.
And in a nutshell, anyone could possibly access that public key, but only the private key
can be used to decrypt the message.
And so most of our most popular cryptographic algorithms include examples such as RSA, Diffie-Hellman
and Elliptic Curve Cryptography.
And these are all asymmetric encryption algorithms, and they are based on three different types
of mathematical problems, namely: factorization, discrete logarithm, and elliptic curve discrete
logarithm.
And these cryptographic algorithms work so well because these mathematical problems that
they're based on are very difficult to solve, but their solutions are very computationally
easy to check.
So, for example, if we wanted to crack RSA, we would need to factorize a 2048 bit integer,
which serves as the public key.
Using a classical computer, this could take potentially millions of years, but quantum
computers are different.
When quantum computers reach full maturity, they have the potential to solve factorization
and discrete logarithm problems much, much faster.
So instead of relying on these classical cryptographic algorithms that have served us so well up
until now, we need to start thinking about quantum safe cryptographic algorithms.
Quantum safe algorithms are based on mathematical problems that neither classical nor quantum
computers can solve efficiently.
They're normally based on geometric problems rather than numerical ones like these.
One example is a mathematical problems that are based on lattices.
So let's have a quick review on lattices.
Lattices could be very simple like this, just a grid of points with lines in between them
that can represent vectors.
And this is just a simple two dimensional lattice.
But lattices could have many more dimensions, and they can also vary in size.
They could be of of even an infinite, infinite size.
And we can use a range of different lattice based problems to develop quantum safe cryptographic
algorithms.
One example is the short vector problem, and the short vector problem essentially works
like this.
Let's say we have a very small, simple lattice like this.
And we can draw some lines in between them that represent the vectors between each the
points.
And the way that I've drawn out here is what is known as a short basis.
But I could draw this exact same lattice in a slightly different way.
And you can kind of see here how the vectors in between each of the points are much longer.
So we would call this a long basis.
So the short vector problem is essentially, let's say we have a point in the middle of
this lattice here or if it we're representing it like this could look like that.
And to solve this problem, we want to find the closest points to A on this lattice.
If we're given a short basis, this can be quite easy to see where the shortest vectors
are between between the points.
But if we're only given a long basis, this becomes much more complicated.
And you can imagine this problem would get even more difficult if we increase the size
of the lattice and if we add many more dimensions.
And so this is quite a simple example, but it really highlights the key point of lattice
based problems, which is that the larger and more complex, the lattice, the more difficult
it is to solve math problems that are based on them, and the more difficult it would be
to crack algorithms that are based on those problems.
It might still be many years before quantum computers can crack algorithms like RSA, but
it also takes a really long time for teams and organizations to adopt and deploy new
cryptographic standards.
The National Institute for Standards and Technology says it can take anywhere from 5 to 15 years
to implement new cryptographic standards.
As you can imagine, it takes time to train developers and cybersecurity professionals
as well as implement the new standards as well.
But NIST has actually been researching different standards already since 2016.
And in July of 2022, they identified four different standards that organizations can
start looking into to become a quantum safe.
And three of those were developed by IBM.
They include CRYSTALS-Dilithium digital signature algorithm, as well as the
Falcon digital signature algorithm.
And lastly, the CRYSTALS-Kyber public key encryption algorithm.
And IBM is already helping organizations become quantum safe.
In 2022, as well as these announcing these cryptographic standards from NIST, they also
launched the First Quantum Safe System with the launch of their Z 16 platform, and they
also offer the IBM Quantum Safe Program, which aims to educate and provide strategic guidance
towards organizations that are looking to become quantum safe, with individualized programs
to help organizations better understand their exposure to cryptographic attacks.
So if you and your team and your organization are ready to start becoming quantum safe,
check out the links in the description to all the things that I mentioned in this video.
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I hope you found this content helpful,
and thank you very much for watching