PonziLens+: Visualizing Bytecode Actions for Smart Ponzi Scheme Identification

TL;DR

PonziLens+ is a visual analytic tool that helps identify smart Ponzi schemes by visualizing execution behaviors of smart contracts, aiding investors and auditors in detecting fraud more reliably.

Contribution

The paper introduces PonziLens+, a novel visualization approach that reveals potential fraudulent behaviors in smart contract bytecodes, enhancing Ponzi scheme detection.

Findings

Effective identification of smart Ponzi schemes demonstrated in case studies

High usability confirmed through user interviews with domain experts

Visualization modules reveal behaviors at multiple levels of detail

Abstract

With the prevalence of smart contracts, smart Ponzi schemes have become a common fraud on blockchain and have caused significant financial loss to cryptocurrency investors in the past few years. Despite the critical importance of detecting smart Ponzi schemes, a reliable and transparent identification approach adaptive to various smart Ponzi schemes is still missing. To fill the research gap, we first extract semantic-meaningful actions to represent the execution behaviors specified in smart contract bytecodes, which are derived from a literature review and in-depth interviews with domain experts. We then propose PonziLens+, a novel visual analytic approach that provides an intuitive and reliable analysis of Ponzi-scheme-related features within these execution behaviors. PonziLens+ has three visualization modules that intuitively reveal all potential behaviors of a smart contract, highlighting fraudulent features across three levels of detail. It can help smart contract investors and auditors achieve confident identification of any smart Ponzi schemes. We conducted two case studies and in-depth user interviews with 12 domain experts and common investors to evaluate PonziLens+. The results demonstrate the effectiveness and usability of PonziLens+ in achieving an effective identification of smart Ponzi schemes.