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Analysis and prevention of adversarial behavior in decentralized exchanges.

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I See You!

Please consider citing our work if you find the work, code, or data helpful.

@inproceedings{ankile2023see,
  title={I See You! Robust Measurement of Adversarial Behavior},
  author={Ankile, Lars and Ferreira, Matheus XV and Parkes, David},
  booktitle={Multi-Agent Security Workshop@ NeurIPS'23},
  year={2023}
}

Data

Swaps Table

Tx Hash Block Block # Pool Addr Token0 Token1 Token0In Token1In sqrtPriceX96Limit

Blocks Table

Block # Initial Liquidity Initial sqrtPriceX96 Liquidity Positions
❌ (WIP)

Potential Data Sources

  • Running a Ethereum full node using geth and interacting with it using web3.py
  • Using Infura.io's full node and API and interact with it using web3.py
  • Use thegraph.com's subgraphs and GrapQL API for Uniswap data, preferably hosted

Data Storage and Querying

Simulating Counterfactual Transaction Sequence

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Analysis and prevention of adversarial behavior in decentralized exchanges.

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