Microsoft Research Podcast - 066 (rerun) - Cryptography for the post-quantum world with Dr. Brian LaMacchia

Episode Date: March 6, 2019

This episode first aired in August of 2018. You know those people who work behind the scenes to make sure nothing bad happens to you, and if they’re really good, you never know who they are because nothing bad happens to you? Well, meet one of those people. Dr. Brian LaMacchia is a Distinguished Engineer and he heads up the Security and Cryptography Group at Microsoft Research. It’s his job to make sure – using up-to-the-minute math – that you’re safe and secure online, both now, and in the post-quantum world to come.Today, Dr. LaMacchia gives us an inside look at the world of cryptography and the number theory behind it, explains what happens when good algorithms go bad, and tells us why, even though cryptographically relevant quantum computers are still decades away, we need to start developing quantum-resistant algorithms right now.  

When I talked with Brian Lamacchia last summer, I was encouraged to learn that while one group at Microsoft Research is working hard to make quantum computing a reality, his security and cryptography group is working hard to make sure that when it is, we're prepared. Whether you heard Brian's podcast back in August, or you're just finding out what it means to be quantum resistant, I know you'll enjoy Episode 38 of the Microsoft Research podcast, Cryptography for the Post-Quantum World. computation showed up, that it would change all of our assumptions, that's yet another example of

how we have to constantly think about what an attacker has available. And if the attacker's resources all of a sudden change, that means they can do more. You're listening to the Microsoft Research Podcast, a show that brings you closer to the cutting edge of technology research and the scientists behind it. I'm your host, Gretchen Huizenga. You know those people who work behind the scenes to make sure nothing bad happens to you? And if they're really good, you never know who they are because nothing bad happens to you? Well, meet one of those people. Dr. Brian Lamacchia is a distinguished engineer, and he heads up the

security and cryptography group at Microsoft Research. It's his job to make sure, using up-to-the-minute math, that you're safe and secure online, both now and in the post-quantum world to come. Today, Dr. Lamacchia gives us an inside look at the world of cryptography and the number theory behind it, explains what happens when good algorithms go bad, and tells us why, even though cryptographically relevant quantum computers are still decades away, we need to start developing quantum-resistant algorithms right now. That and much more on this episode of the Microsoft Research Podcast. Brian Lamacchia, welcome to the podcast.

Thank you. Pleasure to be here. You're a distinguished engineer at Microsoft Research, and you head the security and cryptography team here, which you've called the company's Center of Excellence for Cryptography. What does your group do? What are the big questions you're asking, the big problems you're tackling? What gets you up in the morning? We are, as I said, the Center of Cryptographic Research and Development

for the company. We focus on the hardest problems that the company has that somehow involve cryptography, encryption, digital signatures, things like that. We started a decade ago as a little cryptographic tools team looking for places within the corporate research and development group where we could add value. And we tackled security problems and cryptographic problems for what was then grid computing and became cloud computing, our data centers and security problems all over the place. But for the last three years, we've been focused on this primary work on the upcoming threat of quantum computers,

if they're successful. But then we also do work on other security problems. We spend a lot of time working on the security of Internet of Things devices and how do we make sure that devices inside your home can't be manipulated. We also, I have a member of my team who spends a lot of time on election security and how do you do verified voting and how can we bring the best in cryptographic research to end-to-end verifiable elections. Well, let's do a little bit of a level set as we start here about the field of cryptography. Can you give us a brief history of cryptography? So cryptography is the science of data encryption, and it actually goes back to ancient times. We know that the Romans used very simple forms of ciphers.

The Caesar cipher was used to send information around. And cryptography traditionally was in the military field. And for the longest time, it was what we call in the field symmetric key cryptography. That is, if you and I wanted to exchange secret messages, we would agree on a secret password or a configuration of a mechanical device or something that we used to perform encryption. And then I would use that secret to encrypt information to you. You would get the cipher text, the encrypted information, and you'd use that same secret to decrypt it. So we have the same symmetric shared secret key. And of course, in the 20th century, cryptography started being used more and more to protect wireless communications, right? To protect radio. This is most famously was used in World War II by all sides to protect radio communications. And your listeners probably all know the story of the German Enigma machine, which was a mechanical encryption device, which was broken. Initial research done by Polish mathematicians, and then

it moved to Bletchley Park, and the British did a whole bunch of work under turing and broke the enigma and therefore learned information in secret about encrypted communications all of that's within the realm of the shared key model and then there was a breakthrough for what was called public key cryptography and the difference in public key is each of us who wants to communicate has a pair of keys that are mathematically related, a private key and a public key. And one of those keys you can release to the world. So if I want to encrypt something to you,

I go get your public key and I encrypt it to your public key. I can't decrypt it with your public key. You can decrypt with your private key that matches mathematically. And the same is true for me. And there's a variant of that, which is the digital signature problem, which is I can use a private half to digitally sign a message that anybody can verify it could have only come from me. And we use both of those technologies today. Every time you open a

secure connection in your browser to a website and it's an HTTPS connection, you're doing an encryption digital signature operation. So no nefarious characters can learn your credit card number or the email you're typing if you're talking to a web email, something like that. Let's talk about algorithms. Most people take them for granted and may even be blithely unaware that algorithms are running their lives right now in many, many ways. And I bet if you asked anyone on the street, does math have an expiration or sell-by date, or can an algorithm go bad? They'd just look at you like you're strange. But you've said all cryptographic algorithms weaken, degrade, or break over time.

That's correct. Talk about that. Okay. So unlike many other parts of computer science and computer programming, cryptographic algorithms, which are number theory at their heart, naturally degrade over time as we learn more about how to attack them and as we assume that our attackers have more compute power available to them. So we grade algorithms based on security levels. How much work do we think an attacker has to put in to break an algorithm?

And as we learn more over time, the security level decredes. And algorithms that we think are okay today are not okay tomorrow. And that's really important when you're writing an application or a security protocol or a computer system to understand that the algorithms you're dependent upon today are going to have to change and you can't just use them for the future. It doesn't necessarily have a sell-by date on it, but we are constantly trying to predict what an attacker can do. Sure. And sometimes it's just more compute power being available. And sometimes there's an academic result that all of a sudden changes our understanding of number theory.

I guess the other thing to add is sometimes we get a prediction of when an algorithm is going to break. Like we will see a series of work done in academia where the attacks will come along and they will make further and further progress until something breaks catastrophically. Sometimes we don't get a heads up. I can give you two stories on that if you'd like. I would. Okay. I like stories and I bet our listeners do too. Okay. So a cryptographic hash function is a function that takes any amount of input and hashes it down to a fixed digest size. And for a long time, we used one called MD5, which was invented by Ron Rivest, Professor Rivest at MIT,

the R and the RSA algorithm, and we all thought it was secure. And in 2004, at the annual US Crypto Conference, Professor Xiaoyang Wang from China got up and demonstrated two messages that had the same MD5 hash value. And you're not supposed to ever be able to do that. And she did that. And the fact that she could do that meant that the fundamental security property

of that hash function was no longer any good. And therefore we had to move to another hash function because that one was busted, as far as we care from a cryptographic perspective. But you didn't know that going in. We didn't know that going in, but we knew when we heard it that all of a sudden we were going to get press questions the following morning. And in fact, Josh Benelow from my team and I, we sat at the back of the room and wrote a four-page Q&A for all the folks back at Microsoft to understand what this meant for our products and services going forward. We transitioned to the next hash function that we had, which we called SHA-1. But SHA-1 shared some structural properties, similarities with MD5,

and we figured that it would only be time until SHA-1 fell. And in fact, in March of last year, Mark Stevens at CWI in the Netherlands demonstrated a SHA-1 hash collision. And now SHA-1, of course, hasn't been broken the same way MD5 has. Talk a little bit about how you go about attacking your own stuff. Well, first off, we assume that everything we do is out in the open. And this is a sort of a fundamental thing for my group now. The algorithms themselves are open and published. The code that we ship is open source and available. And from a theoretical perspective, we assume that the attacker has access to all knowledge about the algorithm

and the code and the construction. And the only thing they don't have access to is the secret piece of the key. Okay. So when we try to attack our own algorithms, we are hopefully using the same set of information. And it's how can we deduce the secret key without knowing it? That's part of the analysis and thinking of new techniques and trying them out and trying to get cost estimates for what's doable. If you have a cloud computing infrastructure at your back and, you know, what would it cost to break something of a particular size well let's move on to quantum okay this is a big topic and it's basically what you've been talking about for quite a while, life in a post-quantum world. And that's still a ways out, but as they say in the movie industry, it's coming to a screen near you. Maybe not your screen, but somebody's. And also maybe

not right away. But let's talk about what quantum computing is. I know we did a podcast with Krista Svori, who's all quantum all the time, and that was her perspective. I want to hear from a cryptographer's perspective. What is it? How is it fundamentally or materially different from classical computing? And why does it matter to researchers like you, Brian? Sure. And first off, I should point out that actually Krista gave a great explanation of this during her podcast. And our teams actually work together. We sort of dovetail with each other. But quantum computing is a fundamentally different model of computing. And from our perspective as cryptographers, the key breakthrough in this actually happened in 1994. invented a quantum factoring algorithm. That is, he demonstrated that if you had access to a big enough quantum computer, you could solve a problem in polynomial time. That is, you could factor in polynomial time, which we do not know how to do today or anything close to that with classical

computers. Now, Peter didn't have a quantum computer. We still don't really have big quantum computers. We have very tiny toy ones. But from being able to demonstrate theoretically that if a new fundamental model of computation showed up, that it would change all of our assumptions, that's yet another example of how we have to constantly think about what an attacker has available. And if the attacker's resources all of a sudden change, that means they can do more. So from a cryptographic perspective, quantum computing is yet another model of computation that opens up a different line of attack and a different set of algorithms. And for a lot of the problems that we care about today,

we know that quantum computers will make the attacks faster. And for some of the types of cryptography we've talked about, there are easy mitigations. And for some of the things we're using today, there aren't. And that's sort of what the concern is. You've talked about a big enough quantum computer. Let's go there for a minute. What is big enough? Okay. Well, for your listeners who might be interested, we actually had a paper that appeared at Asia Crypt last December, 2017, working with members of Krista's team on trying to come up with precise estimates for how many logical qubits,

logical quantum bits you need for big enough and what we mean by that is when i think about how difficult it is to break a cryptographic algorithm i talk about that in terms of how big are the keys what's the security parameter for the algorithm so if i am typically doing rsa with two kilobit keys, 2048-bit public keys, that is, the modulus is the product of two primes of each of about 1024 bits, how long does it take to factor that? And that is well beyond anything we could do with sort of all the compute power we have available to us today. But what our paper showed is that if you had just over double that number of quantum bits, just over 4096 quantum bits available in a quantum computer, and those are logical quantum bits that are stable,

you can run Shor's algorithm on it and you can factor that 2048-bit number in polynomial time. So for the types of public key algorithms that we are using today, if we're talking about factoring, typically your RSA keys are two to four kilobits in size, and we need double that number of quantum bits, plus a little bit extra. Basically, from my perspective, things don't get interesting until there's at least a thousand logical quantum bits around on a quantum computer, and really up to 10,000 logical quantum bits. And that is what you call a cryptographically relevant quantum computer? Cryptographically relevant. So in our world, if it's got, say, on the order of 1,000 to 10,000 logical quantum bits, and you can program it, then it becomes cryptographically relevant.

Now you're going to pay attention. And now you got to pay attention. That's where things get catastrophic for the public key algorithms that we're using today, or things get very interesting. But below that, there might be other interesting problems you can solve in chemistry, metallurgy, agriculture, things like that. But what I care about is up in the 1,000 to 10,000 quantum bit range. Let's say quantum does make it big and becomes cryptographically relevant sooner than we think. What's the good news and bad news about a big breakthrough in quantum computing in your mind? The bad news is it means a lot of systems that we use today have to get upgraded and that the algorithms have to

be replaced. And pretty much if you know that an adversary has access to a cryptographically relevant quantum computer, every commonly used public key encryption needs to be replaced. The good news is we've actually got a bunch of candidate replacements. This is work that my team's doing, other folks around the world are doing. And in fact, the U.S. government is running a standardization activity right now to try to pick some new quantum resistantresistant public key encryption and digital signature algorithms. These are classical algorithms. You don't need a quantum computer to run them. These are algorithms that run on classical computers, your laptop, my phone. They can run just like RSA and Diffie-Hellman and the elliptic curve today, they're just based on different hard

number theory problems for which we don't believe there is a fast quantum solution. And an important point here is we don't have any proofs right now that the quantum resistant algorithms that we're all investigating are guaranteed to be quantum resistant. What we know is that there's no known quantum advantage. It's a little bit of a subtle point, but it's important that even for the new algorithms that we and other people around the world are investigating, we don't believe having a cryptographically relevant quantum computer gives you any advantage over having just a cloud full of data center servers to help you. But it's different than

saying we are guaranteed that there is no fast quantum algorithm that we don't know yet. Right. Well, if we situate ourselves in a post-quantum world and we're dealing with quantum resistant algorithms, who has a vested interest in developing these and who are the players at work here? You alluded to that just now. What's the big picture and who's all involved? So there's who's designing them and then who uses them. And if you think about who uses them, well, it's anybody who ships an implementation of a cryptographic library or, you know, inside of an operating system or a device, anybody who's trying to open a secure communications channel over the internet. You need to be able to authenticate the party at the other end, and you need to be able to establish an encrypted

channel and send encrypted information back and forth. That's just common practice, right? As more and more of our communications are happening on the internet in general, we want all of those to be encrypted and private. So everybody who is involved in shipping code like that one way or the other is going to be a customer of quantum resistant algorithms. Who's developing it? It's academic researchers and industry researchers, cryptographers around the world. My team's currently working on four different algorithms right now, and each of them is an international collaboration where we have researchers from industry and academia participating with us on each of those four. And they're different sets. And there's some people that are working on one algorithm with

us and some on another. And these algorithms have different pros and cons when compared. Some are faster than others. Some have smaller key sizes than others. They have different engineering properties. And it's not clear it's a one size fits all sort of thing. My guess is that when the U.S. government standardizes these in hopefully five years, they'll actually choose a small handful of encryption and digital signature algorithms for different use cases because what you want to fit into that smart light switch in your phone that you don't want to be taken over by somebody is very different than what you're going to go put into your laptop. Well, let's talk about that issue right there at the U.S. government, among other governments. There's a competition going on that I would love for you to tell us about and what it involves and what the purpose of it is. Sure. So in 2015, NSA for a decade had been advancing the use of elliptic curve public key technology as part of a suite of commercially available algorithms that they called Suite B, as opposed to Suite A, which are classified algorithms, that they encouraged industry to ship to meet the needs

of the U.S. Department of Defense to protect up to top secret level information. NSA came out in 2015 and said, by the way, if you haven't finished the move to elliptic curve cryptography, you should save your development cycles because we're going to tell you to move to something quantum resistant in the not too distant future. That caused the U.S. National Institutes of Standards and Technology, or NIST, which is the standard setting body for the United States government, not just DoD for all government, to launch a standardization process or a selection process to come up with new algorithms. And NIST has led to very successful public standardization process or a selection process to come up with new algorithms. And NIST has led two very successful public standardization efforts in cryptography in the past. And so NIST has a history of running these types of competitions. And now they've launched this competition. And

in fact, my team is part of four submissions of, I think, about 65 that made it in and are still active, although some of those have since been broken. And what happens now is we are all approved round one candidates. And about this time next year, NIST will announce which of those move on to round two. And during this time, again, everyone's trying to cryptanalyze their own and everybody else's and to say what they can learn about it. And it's up to NIST to whittle it down. And we believe that then there will be a round three in that again, in about five years or so, they will announce some small subset of algorithms that will be approved,

some for public key encryption, some for digital signatures. To be implemented as the standard. As the standard. They will make what's called a FIPS, a Federal Information Processing Standard, to become an international standard because you need international standards for interoperability. We want everyone to basically agree on strong, safe and secure algorithms. So the U.S. government standardization is a step in that process, but it's not the end of it. And this is all aiming towards a post-quantum world. That's right. This is all about getting algorithms in place so that if and when cryptographically relevant quantum computers become real, that we will have algorithms that we will already have transitioned to.

So let's talk about that timeline for a second. Realistically, I've heard from you and others that 15 years, maybe, optimistically 15 years. But why the 15-year workback plan? Why are you working on this now when you've got enough problems in a cloud-based world and all the other things that you've referred to? Well, so that actually is the number I started with in 2015. And what happened was I went to Krista and her team because we had started seeing these signals. And I said, okay, when do you all think that there's a reasonable chance that we'll have a cryptographically relevant quantum computer? And at that time they were saying about 15 years, which was 2030. So I thought, okay, 2030 is a long time away.

And then you start thinking about all the things that you have to do between now and 2030 to effectively upgrade the internet, because that's really what you're talking about, right? You have to research new algorithms. You have to try to attack them. You've got to start a standardization process. You've got to prototype them. You've got to do test deployments. You've got to get them running on your own infrastructure. You've got to upgrade all your customers using your software. And then you have to turn off and decommission the things that will be broken. And when I look at how long it took us as an industry

to do that for the MD5 hash function after Professor Wong's break, and I look at how long it took to do that with the SHA-1 hash function, you know, you add the pieces up, you need about 15 years. So I didn't think we were actually starting too soon. I think we were starting kind of right on time.

And I think we're still about right on time if that 2030 number is still accurate. And it's good to see the progress that's being made within NIST. But I'm still encouraging people to try to move a little bit quicker and to start taking our own prototypes and start deploying in test environments to see how flexible their software is to handle these types of algorithms. And you can do that today. So that leads us into the concept of cryptographic agility, which we referred to earlier. Talk about what that is and why it's necessary. Cryptographic agility basically is an architectural principle in your software that where you use cryptography you do not hard code in a dependency on one or a small number of algorithms it's all about making it very easy to reconfigure your software to use something else for a number of

reasons but everywhere that you have a dependency on a cryptographic algorithm, you want to make sure that you can very easily reconfigure it. If all of a sudden somebody steps up and tells you that they can break yourum world, we want to make sure that all of our software that currently uses public key cryptography is designing in the ability to use a quantum-resistant algorithm, even though we may not know exactly what that algorithm is yet. Or when they're going to need it.

But we can start making sure that all our systems have that agility today. And part of the reason that my team doesn't just do the theoretical work, but we put out these high-performant, constant-time, side-channel resistant implementations, is so that we can actually integrate them into the commonly used security protocols today and show how those algorithms would work. And that's why you can actually go run some of the most common algorithms like TLS or SSH or VPNs with our post-quantum algorithms in the mix.

Talk about this concept of record now, break later, or as you phrased it, record now, exploit later. Why should we be worried about somebody getting encrypted data that there's no way they can unencrypt right now. So this is a real worry. And in fact, it's another reason why even without quantum computers existing today, you may want to deploy post-quantum right now. You have to assume that if you're sending sensitive data over a public network, that your adversary, whomever your adversary is, will record that data, has access to the public channel. That's why you're encrypting it in the first place. But data storage is cheap.

Recording is cheap. So if you and I are communicating over encrypted connection, we have to assume that our mutual adversary is recording that traffic and storing it away for the day in the future when quantum computers are real, and the adversary can come back and use the quantum computer in the future to learn about what you and I talked about on the Encrypted Channel today. Now, if we're exchanging recipes or something that we don't think has a lot of long-term secret value, that may not matter. Well, mine do. Okay, well, mine don't, okay, but you know. But let's say that you are a nation state and you're sending information that's classified. And those things typically have, I understand, a 30 or 50 year or longer time horizon, a security horizon. And it's not just national government level data. Let's say that you're in the pharmaceutical industry where some of your research is going to have a 20 or 30 year security horizon because that's the patent

protection on the drug or that you are in any industry where the information's got a long security horizon. If this time in which you need the information to be protected is longer than when we think quantum computers are going to show up, you have to assume that information is going to be recorded and broken when an attacker has access to a quantum computer. And so your protection horizon is truncated by the appearance of quantum computers if you're only using classical algorithms. So if you're trying to protect data for, say, 50 years today, you should be using a combination of the best classical schemes that we have right now and a post-quantum scheme to try to give you some protection beyond the advent of

quantum computers. That's the safest thing. It's what we call a hybrid scheme, where you use the best classical schemes that we have many, many decades of knowledge about from studying and add in some new protection. Well, let's say that does scare me and I want to have that post-quantum algorithm or quantum resistant algorithm. Can I get it? Yeah. In fact, all of the submissions to NIST, as part of the submission, everybody had to make open source implementations available to their algorithms. In fact, your listeners can go out to GitHub and they can go download all of our code and you can go get those libraries today

and start using them. And if you happen to be a customer of OpenSSL, a very common TLS implementation, or OpenSSH or OpenVPN, you can run that today. We even built a nice little demonstration device. We took a little Raspberry Pi and we turned it into a combination Wi-Fi hotspot and post-quantum VPN endpoint. So I can take that

with me anywhere in the world and it sets up a VPN to a Linux machine running in Azure. That is my other endpoint and I can connect wirelessly to the hotspot in my hotel room and I've got a post-quantum tunnel back to the Azure cloud. And all I've got is a Starbucks open and unsecured network. You probably want a little bit more than that. I probably do, but yeah, I just hang out with you more. Speaking of the things that scare me, you gave a talk recently that you subtly titled

How to Prepare for Certain Catastrophe. And that's a perfect setup for the question I ask all my guests, which is, is there anything that keeps you up at night? Yeah. So the thing that keeps me up at night is that, say, Krista Svore and her team are going to be successful sooner rather than later. And by that, I mean that we're going to see quantum computers show up more quickly than we anticipate. That the qubit construction challenges and the scaling problems will get solved by the very smart people working on them faster than we can standardize and deploy defenses. There's this arms race going on between the quantum computing folks who are trying to build the quantum computers and the post quantum cryptographers trying to make sure the defenses are out there before the quantum computing people are successful. That's what keeps me up at night, but it's a good problem to have.

How'd you wind up doing cryptography research? What was your path to MSR? It started as an undergrad at MIT. I was a co-op student at AT&T Bell Labs. And during my junior year, I took an undergraduate class in cryptography from Professor Shafi Goldwasser, who is now a Turing Award winner for her work with Sylvia McCauley in cryptography. And cryptography is this weird area of computer science that is taking some of the purest mathematics and number theory and applying it to real-world practical privacy and security problems. And that was my jam. And at the end of the class, I asked Shafi if she could recommend some people at Bell Labs

who were doing cryptography for my next summer assignment. And I was fortunate enough that she pointed me to Andrew Adlizgo, who turned out to be my mentor for my master's thesis. And I did a couple summers and a master's thesis at Bell Labs in breaking what were then called Knapsack cryptosystems, which are no longer used because we've pretty much broken them completely, but they were a type of public key crypto system that was being studied at the time. And that led to graduate school. Actually, my PhD was in artificial intelligence.

And I went back to Bell Labs because they were looking for computer scientists with an economic, legal, or social bent to look at public policy computer science research. But the work I was doing was interesting to Microsoft, and I got recruited out into the product teams. And then got recruited into a group to become a cryptographic architect for some work we were doing on trusted computing very early on. And in 2005, I ended up over in corporate R&D working on this little, what I'd call a security SWAT team, basically for one of our former CTOs. And in 2009, we got reorganized into Microsoft Research into this new applied division. And that's still kind of where I am. And I have a mix of researchers and engineers, you know, developers, program managers on my team. And everything that we do is both about furthering the academic field, as well as putting open source implementations of our algorithms and protocols out

for everyone else to use. Right. Well, and that's a beautiful segue to, as we close, give some parting advice to researchers who are listening to this podcast, potential researchers, what might be on the horizon for them that you think would be good hard problems to work on from your perspective in the sort of math-intensive side of computer science research? Well, here's the easy softball one. If there's people out there that are interested in cryptanalysis, there's 60 targets, very easy targets in the NIST competition for people to go do cryptanalytic work because all of these algorithms are under consideration. And the more we know about something, the better. One of the reasons I would not recommend that we just solely

move to only post-quantum algorithms today is that none of these algorithms have been studied as long as, say, RSA and elliptic curve-based things. So that's why I actually think for the first about decade of deployment, we're going to do hybrid schemes where we'll use both. That probably means you end up digitally signing things with two keys, one classical and one post-quantum. So there's a lot of cryptanalytic work there. I think we're still learning about leakage, ways in which our implementations on software and hardware leak information that makes it easy to break. You're not breaking the mathematics. You're effectively bypassing the mathematics by inferring bits of a secret key through physical properties of the device. And we have to use physical devices to work on this. And that's a very rich area. Another area that we're starting to do a little bit of work on, but I think held a lot of promise is in formally verified implementations. And I think that's a very rich area to doing work on within the cryptographic application space. So there's a lot of still fruitful areas of exploration and research.

Oh, absolutely. My team did some work back in 2008 and 2009 on distributed key management. And that's for how do you share secrets securely among, say, every machine and every rack in a data center without having somebody plug a USB device into every machine manually. And there's some non-trivial problems in that space. Key management of cryptographic keys is a very important problem, and it doesn't tend to get as much attention as it should. And I think that's another fruitful space. I have to ask you one more question. Sure. How do you manage your passwords? Perfectly fine question. I have a couple of what I consider very high value passwords, which are all in my head.

For all the typical website logins, I use a password manager. So that plugs into the browser. And then that is combined with a master password that unlocks that vault and a physical device that I plug in. So I do two factor authenticationactor authentication, and everybody should. Brian LaMacchia, thank you for talking to us today. It's been really, really interesting. It's been my pleasure. Thank you very much for having me.

To learn more about Dr. Brian LaMacchia and how Microsoft is working to ensure online security and privacy in a post-quantum future, visit Microsoft.com slash research.