Next up I want to introduce Elaine Shi and Andrew Miller from University of Maryland. Andrew is also on the zerocash team.

Okay. I am an assistant professor at the University of Maryland. We all believe that cryptocurrency is the way of the future and smart contracts. So students in the future have to program smart contracts.

So that's what I did. I asked some students to program some smart contracts. I am going to first give some quick background and then I will talk about the insights that we gained from this lab. Okay.

So I asked my students to work in groups of 4. This is the first time that this type of lab has been attempted. I asked one of my PhD students to advise each project group.

In the first phase we had the proposal phase where students developed an application of choice on top of Ethereum's programming language called serpent. As the lab went on, we realized that we needed a second phase, the amendment critique phase.

In the second phase, the instructors- Andrew Miller and myself, and the graduate TAs. We gave feedback about the applications they created. I asked the students to form groups and critique each other's applications.

Based on the feedback, the students amended their designs.

The outcome is that there is good news and bad news. The good news was that this was an aspiring experience. Both the students and the instructors learned tremendously throughout the process. Some students said they really enjoyed learning about cryptocurrency. All project groups did a really impressive job.

The bad news is that some students didn't enjoy the premature nature of Ethereum's language. This language is in development. It's poorly documented and some groups had difficulty setting things up and getting their application to run on top of this language.

The students created many interesting applications like games where players play for money, like RPS, Russian roulette, and so on. Escrow services. Auctions. One group created a parking meter application. Some groups created stock market applications.

Okay. So what are the lessons learned? At the end of phase 1, we actually realized that many groups programmed contracts which had problems with them. They were insecure. And essentially as weak now, security is difficult. When you write a traditional program, we know all the ways you can mess up. Here we are programming smart contracts, it turns out there are new ways to mess up and create bad contracts. Okay.

So as we all know, smart contracts have high value transaction values. So the security is important. If I am a user, I want to know that my money will be protected if I send money to the contract. Let me give you some examples. Partly the purpose of this is to walk through step by step about how to create a safe cryptocurrency contract.

Before I do that, let's first try to have a very quick overview of the programming model of Ethereum. Okay. In Ethereum, there's a key concept called a contract. And the contract would interact with different users. So the contract can both have both storage and program logic. Okay. A contract can store messages and money. It has some Turing complete program logic it can execute. In Ethereum, the idea is that the data of the contract is going to be stored on the public blockchain. And the program logic of the contract is going to be executed by all miners on the network. Okay. So assume the underlying cryptocurrency protocol maintains its security properties, then one way to think about the contract is to think of a trusted third party without privacy. Okay, so is it trusted? It is because, assume the entire network reaches consensus, and assume that you assume the protocol is secure such that the majority of the miners will execute an honest reference client. Why is there no privacy? Well, everything is public and the whole blockchain is public and all messages are public. Okay.

So the contract would interact with the users and the users can send and receive money to and from the contract and they can send and receive messages from the contract. Okay. So I am going to use a rock paper scissors example to show some mistakes.

So here is how you would write a RPS contract. There are three entry points to the contract. At player, input and winner. Let's imagine a two person contract. "At player" would register and then send money to the contract. So the contract would store their money and their identity. That's the first step. The second step of the game is a function called input. This is where the players, the players need to choose something to play, so I choose paper, so I choose scissors, this is where players send inputs to the contract. The contract will store their inputs. In the final step, the contract will decide the winner and send all the money to the winner. That's a high-level overview.

For instance, here's a typical at player function that students wrote. If you look at the function a little more carefully, it's very simple. Self dot storage is the contract storage and when the contract receives the message it will basically first see whether the amount of money associated with the transaction is bigger than 1000 ethers. Then it will see if player 1 has been created. If not, the contract would record player1's identity and then it would store the money on to the contract which is the storage winnings equal to .. plus message value... Similarly, when player two enters. So I hope it is clear what this function does.

What's the problem with this function? Does anyone see the problem? If you look at this a little more carefully you will realize that what if a third player tries to join the contract. What if I make a mistake where I send less than 1000 ethers? The contract eats the money. So if you are the user and you are dealing with this contract, you would have to be very carefully. You do not want to be the third player to send money. There can be someone concurrently attempting to send money in the same epic. The users are unprotected.

So here's a second type of mistake. The input function where players send their choices. Here the program is very simple. It looks at whether this is player1 or player2 and then it records the player's choice. What's wrong with this? Okay, if you think about it a little more carefully, it will become immediate that the problem here is that the players are sending their choices in cleartext to the contract. So the messages are sent in the clear and the player's choice is stored in plaintext in the contract. So if I am a player, what makes sense for me is to wait for the other player to send their input, and then for me to decide what I should send. So that's broken.

How do you fix this? There's a simple technique where you make a commitment. You make a commitment, it is cryptographically hiding, then in the second part you would open your commitment. That's what you want to do.

Suppose you do the right thing and use a cryptographic commitment. There are still ways you can mess up. Imagine that the players have sent their committed inputs to the contract. In a later phase they would open their commitment. This function is where they open their commitment. The detailed code is not too important. What is the problem here? Okay, so here is another problem. Essentially let's say you and I are playing the game, you open the commitment and I see that I am losing. At this moment I have no incentive to open my commitment. It becomes stuck in the contract. If you are the winner then you wont get the winnings. So that's pretty bad.

So this brings us to the third class of mistakes which is incentive compatibility. You want to create contracts that are incentive compatible. You can introduce a deposit structure to the contract where you require players to deposit money to play, and then if they don't open their commitments within a certain amount of time then their deposit will be sent to the other player.

This was an interesting experience, we went back and forth to get the students to fix their contracts. What's coming up soon is that we are going to release some online course material for programming smart contracts. I have hired my undergrad students back to create a detailed manual to write the instructions. We will setup a VM where we are running pyethereum and we will have this step by step lab where we coach students how to create these smart contracts and what kind of mistakes to avoid. So if you are a professor and you want to do a lab like this, then check our online course material and use the virtual machine we have setup.

In this course material we will have some other more.. which I am not going to cover here.. they are related to the specifics to the ethereum or serpent language.

Andrew will now give a quick announcement. Hi everyone, thanks. I have no particular, where are my other slides. Thank you. I want to give you, I have no transition for this, I want to give a short update on another project. This is one of my pet research projects. Kicking around since 2013.

This is just a short announcement. Non-outsourceable mining puzzles. The motivation here is that everyone knows that Bitcoin's value is decentralization. And we aren't quite getting the decentralization we want. There are extremely influential mining pools. There are some large industrial miners. They sell shares of mining power to other people that may have been Bitcoin mining on their own but instead they are hiring some central organization to do their mining for them. So I wanted to investigate if it was possible to have a technical disincentive against this, so a technical measure to prevent this and restore Bitcoin to a more decentralized ideal.

The observation that makes this work is that the reason why pools are able to exist in the first place is that the members don't have to trust each other. There's a protocol where you send shares. The goal of this research is to propose a new puzzle that prevents that protocol to work. Whoever does the block and finds the solution, they have to have a private key to take the reward for them. To do the work you have to have a private key and you can take that reward if you have it. We have a stronger version where you can take the reward and you can avoid getting caught or punished. How does that work? Uses magic cryptography using zero knowledge snarks. Someone else will give an intro to zkSnarks later. There's this technical way to steal the puzzle solution for yourself if you find it. This is an implementation of this, it's new, it takes only 14 seconds to create one of these puzzle stealing proofs using the libsnarks library. It would take about $40 of ec2 time.

I got a lot of great feedback. There are some conflicting challenges to integrate this. Mining pools going away, mining solo is hard unless you have lots of hashpower or hashrate. There has been some work recently on the GHOST protocol and other proposals for getting the time between blocks down really fast, so maybe we can include that. Hosted mining has other things they can do, like getting you this much money every week so that there's no way to hide it, and they could use the same shares protocol to prove how well they are doing. You want to have fast low value blocks to prevent hosted mining from absorbing the risk themselves. So we have put together a different incentive scheme like State lotteries. Every time you make an attempt at a puzzle, you have a chance at a low value prize or a high value prize. The low value prize is for variance, and high value is so that big centralization wont be able to take money, and to prevent someone from skimming from the top.

This is compatible with existing Bitcoin mining equipment. We give a transformation for the non-outsourceable puzzle variant. You can make a non-outsourceable version of an ASIC resistant puzzle. This is all in the new version of the paper if you just search for the word non-outsourceable you will find it, that's all, thank you.

Q: Can we use automated techniques for testing to detect these bugs?

A: You asked the right question. That's our new research program. I would be happy to talk more about that offline.

Q: Hi, so, when I looked at the initial presentation, I was reminded in the legal system, if you don't commit, if you don't answer a claim you default and you also lose. It looked a little static. If people noticed the flaw, they could play along for low stakes, and then wait until the stakes get big. Have you done dynamic iterations of these experiments?

A: So far we have run this lab once. We definitely want to repeat it. That's why we are also creating this online course material.

Q: So if you noticed a flaw and it was in a dynamic situation, you might withhold the fact that you noticed the flaw and then play along for a while. And then ponzi schemers put up small returns, but when the money gets big they walk away. There seems to be a game play element.

A: We did not see concrete instances of this. Cases of this like would be very interesting to us. I think this proves that programming smart contracts is very tricky. There are all of these things you have to get right, these things don't exist in traditional programming. This can be an interesting place where disciplines cross each other. You can have game theory, incentives, mechanism design meets programming language research. It would be very interesting to try to design tools to get programmers to do this right.