We present CanDID, a platform for practical, user-friendly realization of decentralized identity, the idea of empowering end users with management of their own credentials.While decentralized identity promises to give users greater control over their private data, it burdens users with management of private keys, creating a significant risk of key loss. Existing and proposed approaches also presume the spontaneous availability of a credential-issuance ecosystem, creating a bootstrapping problem. They also omit essential functionality, like resistance to Sybil attacks and the ability to detect misbehaving or sanctioned users while preserving user privacy.CanDID addresses these challenges by issuing credentials in a user-friendly way that draws securely and privately on data from existing, unmodified web service providers. Such legacy compatibility similarly enables CanDID users to leverage their existing online accounts for recovery of lost keys. Using a decentralized committee of nodes, CanDID provides strong confidentiality for user’s keys, real-world identities, and data, yet prevents users from spawning multiple identities and allows identification (and blacklisting) of sanctioned users.We present the CanDID architecture and report on experiments demonstrating its practical performance.

Blockchains, and specifically smart contracts, have promised to create fair and transparent trading ecosystems.Unfortunately, we show that this promise has not been met. We document and quantify the widespread and rising deployment of arbitrage bots in blockchain systems, specifically in decentralized exchanges (or "DEXes"). Like high-frequency traders on Wall Street, these bots exploit inefficiencies in DEXes, paying high transaction fees and optimizing network latency to frontrun, i.e., anticipate and exploit, ordinary users' DEX trades.We study the breadth of DEX arbitrage bots in a subset of transactions that yield quantifiable revenue to these bots. We also study bots' profit-making strategies, with a focus on blockchain-specific elements. We observe bots engage in what we call priority gas auctions (PGAs), competitively bidding up transaction fees in order to obtain priority ordering, i.e., early block position and execution, for their transactions. PGAs present an interesting and complex new continuous-time, partial-information, game-theoretic model that we formalize and study. We release an interactive web portal, frontrun.me, to provide the community with real-time data on PGAs. We additionally show that high fees paid for priority transaction ordering poses a systemic risk to consensus-layer security. We explain that such fees are just one form of a general phenomenon in DEXes and beyond-what we call miner extractable value (MEV)-that poses concrete, measurable, consensus-layer security risks. We show empirically that MEV poses a realistic threat to Ethereum today. Our work highlights the large, complex risks created by transaction-ordering dependencies in smart contracts and the ways in which traditional forms of financial-market exploitation are adapting to and penetrating blockchain economies.