Jason Teutsch

Jason Teutsch

Nakamoto consensus, the protocol underlying Bitcoin, has the potential to secure a new class of systems which agree on non-mathematical truths. As an example of this capability, we propose a design for a trustless, data availability oracle. This exposition reduces the problem of determining whether or not a registered datum is publicly available to the problem of constructing a network in which either almost all nodes can download a given datum, or almost none of them can.

Jason Teutsch, Michael Straka, Dan Boneh

In December 2015, a bounty emerged to establish both reliable communication and secure transfer of value between the Dogecoin and Ethereum blockchains. This prized "Dogethereum bridge" would allow parties to "lock" a DOGE coin on Dogecoin and in exchange receive a newly minted WOW token in Ethereum. Any subsequent owner of the WOW token could burn it and, in exchange, earn the right to "unlock" a DOGE on Dogecoin. We describe an efficient, trustless, and retrofitting Dogethereum construction which requires no fork but rather employs economic collateral to achieve a "lock" operation in Dogecoin. The protocol relies on bulletproofs, Truebit, and parametrized tokens to efficiently and trustlessly relay events from the "true" Dogecoin blockchain into Ethereum. The present construction not only enables cross-platform exchange but also allows Ethereum smart contracts to trustlessly access Dogecoin. A similar technique adds Ethereum-based smart contracts to Bitcoin and Bitcoin data to Ethereum smart contracts.

Jason Teutsch, Vitalik Buterin, Christopher Brown

Ethereum has emerged as a dynamic platform for exchanging cryptocurrency tokens. While token crowdsales cannot simultaneously guarantee buyers both certainty of valuation and certainty of participation, we show that if each token buyer specifies a desired purchase quantity at each valuation then everyone can successfully participate. Our implementation introduces smart contract techniques which recruit outside participants in order to circumvent computational complexity barriers.

Jason Teutsch, Christian Reitwießner

Bitcoin and Ethereum, whose miners arguably collectively comprise the most powerful computational resource in the history of mankind, offer no more power for processing and verifying transactions than a typical smart phone. The system described herein bypasses this bottleneck and brings scalable computation to Ethereum. Our new system consists of a financial incentive layer atop a dispute resolution layer where the latter takes form of a versatile "verification game." In addition to secure outsourced computation, immediate applications include decentralized mining pools whose operator is an Ethereum smart contract, a cryptocurrency with scalable transaction throughput, and a trustless means for transferring currency between disjoint cryptocurrency systems.

Jason Teutsch, Sami Mäkelä, Surya Bakshi

We outline a token model for Truebit, a retrofitting, blockchain enhancement which enables secure, community-based computation. The model addresses the challenge of stable task pricing, as raised in the Truebit whitepaper, without appealing to external oracles, exchanges, or hierarchical nodes. The system's sustainable economics and fair market pricing derive from a mintable token format which leverages existing tokens for liquidity. Finally, we introduce a governance layer whose lifecycles culminates with permanent dissolution into utility tokens, thereby tending the network towards autonomous decentralization.

Sanjay Jain, Prateek Saxena, Frank Stephan et al.

The present paper introduces a practical protocol for provably secure, outsourced computation. Our protocol minimizes overhead for verification by requiring solutions to withstand an interactive game between a prover and challenger. For optimization problems, the best or nearly best of all submitted solutions is expected to be accepted by this approach. Financial incentives and deposits are used in order to overcome the problem of fake participants.

Robert F. Erbacher, Trent Jaeger, Nirupama Talele et al.

Motivated by an application in network security, we investigate the following "linear" case of Directed Mutlicut. Let $G$ be a directed graph which includes some distinguished vertices $t_1, \ldots, t_k$. What is the size of the smallest edge cut which eliminates all paths from $t_i$ to $t_j$ for all $i < j$? We show that this problem is fixed-parameter tractable when parametrized in the cutset size $p$ via an algorithm running in $O(4^p p n^4)$ time.