Lanturn: Measuring Economic Security of Smart Contracts Through Adaptive Learning
Kushal Babel, Mojan Javaheripi, Yan Ji, Mahimna Kelkar, Farinaz Koushanfar, Ari Juels
Abstract
We introduce Lanturn: a general purpose adaptive learning-based framework for measuring the cryptoeconomic security of composed decentralized-finance (DeFi) smart contracts. Lanturn discovers strategies comprising of concrete transactions for extracting economic value from smart contracts interacting with a particular transaction environment. We formulate the strategy discovery as a black-box optimization problem and leverage a novel adaptive learning-based algorithm to address it.
Topics & Concepts
Leverage (statistics)Database transactionComputer scienceSmart contractAdaptive learningComputer securityArtificial intelligenceDatabaseBlockchain Technology Applications and SecurityFinancial Markets and Investment StrategiesComplex Systems and Time Series Analysis