A Faster, More Efficient Cryptocurrency

Design reduces by 99 percent the data users need to join the network and verify transactions.


MIT researchers have developed a new cryptocurrency that drastically reduces the data users need to join the network and verify transactions — by up to 99 percent compared to today’s popular cryptocurrencies. This means a much more scalable network.

Cryptocurrencies, such as the popular Bitcoin, are networks built on the blockchain, a financial ledger formatted in a sequence of individual blocks, each containing transaction data. These networks are decentralized, meaning there are no banks or organizations to manage funds and balances, so users join forces to store and verify the transactions.

But decentralization leads to a scalability problem. To join a cryptocurrency, new users must download and store all transaction data from hundreds of thousands of individual blocks. They must also store these data to use the service and help verify transactions. This makes the process slow or computationally impractical for some.

In a paper being presented at the Network and Distributed System Security Symposium next month, the MIT researchers introduce Vault, a cryptocurrency that lets users join the network by downloading only a fraction of the total transaction data. It also incorporates techniques that delete empty accounts that take up space, and enables verifications using only the most recent transaction data that are divided and shared across the network, minimizing an individual user’s data storage and processing requirements.

In experiments, Vault reduced the bandwidth for joining its network by 99 percent compared to Bitcoin and 90 percent compared to Ethereum, which is considered one of today’s most efficient cryptocurrencies. Importantly, Vault still ensures that all nodes validate all transactions, providing tight security equal to its existing counterparts.

“Currently there are a lot of cryptocurrencies, but they’re hitting bottlenecks related to joining the system as a new user and to storage. The broad goal here is to enable cryptocurrencies to scale well for more and more users,” says co-author Derek Leung, a graduate student in the Computer Science and Artificial Intelligence Laboratory (CSAIL).

Joining Leung on the paper are CSAIL researchers Yossi Gilad and Nickolai Zeldovich, who is also a professor in the Department of Electrical Engineering and Computer Science (EECS); and recent alumnus Adam Suhl ’18.

Vaulting over blocks

Each block in a cryptocurrency network contains a timestamp, its location in the blockchain, and fixed-length string of numbers and letters, called a “hash,” that’s basically the block’s identification. Each new block contains the hash of the previous block in the blockchain. Blocks in Vault also contain up to 10,000 transactions — or 10 megabytes of data — that must all be verified by users. The structure of the blockchain and, in particular, the chain of hashes, ensures that an adversary cannot hack the blocks without detection.

New users join cryptocurrency networks, or “bootstrap,” by downloading all past transaction data to ensure they’re secure and up to date. To join Bitcoin last year, for instance, a user would download 500,000 blocks totaling about 150 gigabytes. Users must also store all account balances to help verify new users and ensure users have enough funds to complete transactions. Storage requirements are becoming substantial, as Bitcoin expands beyond 22 million accounts.

The researchers built their system on top of a new cryptocurrency network called Algorand — invented by Silvio Micali, the Ford Professor of Engineering at MIT — that’s secure, decentralized, and more scalable than other cryptocurrencies.

With traditional cryptocurrencies, users compete to solve equations that validate blocks, with the first to solve the equations receiving funds. As the network scales, this slows down transaction processing times. Algorand uses a “proof-of-stake” concept to more efficiently verify blocks and better enable new users join. For every block, a representative verification “committee” is selected. Users with more money — or stake — in the network have higher probability of being selected. To join the network, users verify each certificate, not every transaction.

But each block holds some key information to validate the certificate immediately ahead of it, meaning new users must start with the first block in the chain, along with its certificate, and sequentially validate each one in order, which can be time-consuming. To speed things up, the researchers give each new certificate verification information based on a block a few hundred or 1,000 blocks behind it — called a “breadcrumb.” When a new user joins, they match the breadcrumb of an early block to a breadcrumb 1,000 blocks ahead. That breadcrumb can be matched to another breadcrumb 1,000 blocks ahead, and so on.

“The paper title is a pun,” Leung says. “A vault is a place where you can store money, but the blockchain also lets you ‘vault’ over blocks when joining a network. When I’m bootstrapping, I only need a block from way in the past to verify a block way in the future. I can skip over all blocks in between, which saves us a lot of bandwidth.”

Divide and discard

To reduce data storage requirements, the researchers designed Vault with a novel “sharding” scheme. The technique divides transaction data into smaller portions — or shards — that it shares across the network, so individual users only have to process small amounts of data to verify transactions.

To implement sharing in a secure way, Vault uses a well-known data structure called a binary Merkle tree. In binary trees, a single top node branches off into two “children” nodes, and those two nodes each break into two children nodes, and so on.

In Merkle trees, the top node contains a single hash, called a root hash. But the tree is constructed from the bottom, up. The tree combines each pair of children hashes along the bottom to form their parent hash. It repeats that process up the tree, assigning a parent node from each pair of children nodes, until it combines everything into the root hash. In cryptocurrencies, the top node contains a hash of a single block. Each bottom node contains a hash that signifies the balance information about one account involved in one transaction in the block. The balance hash and block hash are tied together.

To verify any one transaction, the network combines the two children nodes to get the parent node hash. It repeats that process working up the tree. If the final combined hash matches the root hash of the block, the transaction can be verified. But with traditional cryptocurrencies, users must store the entire tree structure.

With Vault, the researchers divide the Merkle tree into separate shards assigned to separate groups of users. Each user account only ever stores the balances of the accounts in its assigned shard, as well as root hashes. The trick is having all users store one layer of nodes that cuts across the entire Merkle tree. When a user needs to verify a transaction from outside of their shard, they trace a path to that common layer. From that common layer, they can determine the balance of the account outside their shard, and continue validation normally.

“Each shard of the network is responsible for storing a smaller slice of a big data structure, but this small slice allows users to verify transactions from all other parts of network,” Leung says.

Additionally, the researchers designed a novel scheme that recognizes and discards from a user’s assigned shard accounts that have had zero balances for a certain length of time. Other cryptocurrencies keep all empty accounts, which increase data storage requirements while serving no real purpose, as they don’t need verification. When users store account data in Vault, they ignore those old, empty accounts.

Author: Rob Matheson
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The first “social network” of brains lets three people transmit thoughts to each other’s heads

BrainNet allows collaborative problem-solving using direct brain-to-brain communication.

The ability to send thoughts directly to another person’s brain is the stuff of science fiction. At least, it used to be.

In recent years, physicists and neuroscientists have developed an armory of tools that can sense certain kinds of thoughts and transmit information about them into other brains. That has made brain-to-brain communication a reality.

These tools include electroencephalograms (EEGs) that record electrical activity in the brain and transcranial magnetic stimulation (TMS), which can transmit information into the brain.

In 2015, Andrea Stocco and his colleagues at the University of Washington in Seattle used this gear to connect two people via a brain-to-brain interface. The people then played a 20 questions–type game.

An obvious next step is to allow several people to join such a conversation, and today Stocco and his colleagues announced they have achieved this using a world-first brain-to-brain network. The network, which they call BrainNet, allows a small group to play a collaborative Tetris-like game. “Our results raise the possibility of future brain-to-brain interfaces that enable cooperative problem-solving by humans using a ‘social network’ of connected brains,” they say.

The technology behind the network is relatively straightforward. EEGs measure the electrical activity of the brain. They consist of a number of electrodes placed on the skull that can pick up electrical activity in the brain.

A key idea is that people can change the signals their brain produces relatively easily. For example, brain signals can easily become entrained with external ones. So watching a light flashing at 15 hertz causes the brain to emit a strong electrical signal at the same frequency. Switching attention to a light flashing at 17 Hz changes the frequency of the brain signal in a way an EEG can spot relatively easily.

TMS manipulates brain activity by inducing electrical activity in specific brain areas. For example, a magnetic pulse focused onto the occipital cortex triggers the sensation of seeing a flash of light, known as a phosphene.

Together, these devices make it possible to send and receive signals directly to and from the brain. But nobody has created a network that allows group communication. Until now.

Stocco and his colleagues have created a network that allows three individuals to send and receive information directly to their brains. They say the network is easily scalable and limited only by the availability of EEG and TMS devices.

The proof-of-principle network connects three people: two senders and one person able to receive and transmit, all in separate rooms and unable to communicate conventionally. The group together has to solve a Tetris-like game in which a falling block has to be rotated so that it fits into a space at the bottom of the screen.

The two senders, wearing EEGs, can both see the full screen. The game is designed so the shape of the descending block fits in the bottom row either if it is rotated by 180 degrees or if it is not rotated. The senders have to decide which and broadcast the information to the third member of the group.

To do this, they vary the signal their brains produce. If the EEG picks up a 15 Hz signal from their brains, it moves a cursor toward the right-hand side of the screen. When the cursor reaches the right-hand side, the device sends a signal to the receiver to rotate the block.

The senders can control their brain signals by staring at LEDs on either side of the screen—one flashing at 15 Hz and the other at 17 Hz.

The receiver, attached to an EEG and a TMS, has a different task. The receiver can see only the top half of the Tetris screen, and so can see the block but not how it should be rotated. However, the receiver receives signals via the TMS from each sender, saying either “rotate” or “do not rotate.”

The signals consist of a single phosphene to indicate the block must be rotated or no flash of light to indicate that it should not be rotated. So the data rate is low—just one bit per interaction.

Having received data from both senders, the receiver performs the action. But crucially, the game allows for another round of interaction.

The senders can see the block falling and so can determine whether the receiver has made the right call and transmit the next course of action—either rotate or not—in another round of communication.

This allows the researchers to have some fun. In some of the trials they deliberately change the information from one sender to see if the receiver can determine whether to ignore it. That introduces an element of error often reflected in real social situations.

But the question they investigate is whether humans can work out what to do when the data rates are so low. It turns out humans, being social animals, can distinguish between the correct and false information using the brain-to-brain protocol alone.

That’s interesting work that paves the way for more complex networks. The team says the information travels across a bespoke network set up between three rooms in their labs. However, there is no reason why the network cannot be extended to the Internet, allowing participants around the world to collaborate.

“A cloud-based brain-to-brain interface server could direct information transmission between any set of devices on the brain-to-brain interface network and make it globally operable through the Internet, thereby allowing cloud-based interactions between brains on a global scale,” Stocco and his colleagues say. “The pursuit of such brain-to-brain interfaces has the potential to not only open new frontiers in human communication and collaboration but also provide us with a deeper understanding of the human brain.”

Author: Emerging Technology from the arXiv
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