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MEV Detection Using zkGraphs

A POC on Proving that a user's behavior such as Swap was potentially harmed by an MEV bot

Analysis Process

  1. Extraction of Reserve Values:

    • extraction of reserve values of specific tokens before and after the suspected transactions from Sync function.

  2. Price Calculation:

    • Prices were computed based on the token reserves.

  3. Comparison and MEV Detection:

    • A significant price difference between pre- and post-transaction states was used as an indicator of MEV.

  4. Threshold Application:

    • We set a threshold to distinguish normal fluctuations from potential MEV activities.

Conclusion

Using zkGraphs, we have demonstrated a robust method to detect and prove MEV in blockchain transactions. This approach enhances transparency and security in blockchain networks by identifying potentially exploitative behaviors.