Skip to Main Content
HBS Home
  • About
  • Academic Programs
  • Alumni
  • Faculty & Research
  • Baker Library
  • Giving
  • Harvard Business Review
  • Initiatives
  • News
  • Recruit
  • Map / Directions
Faculty & Research
  • Faculty
  • Research
  • Featured Topics
  • Academic Units
  • …→
  • Harvard Business School→
  • Faculty & Research→
Publications
Publications
  • 2025
  • Working Paper

Incentive-Compatible Recovery from Manipulated Signals, with Applications to Decentralized Physical Infrastructure

By: Jason Milionis, Jens Ernstberger, Joseph Bonneau, Scott Duke Kominers and Tim Roughgarden
  • Format:Print
  • | Language:English
  • | Pages:19
ShareBar

Abstract

We introduce the first formal model capturing the elicitation of unverifiable information from a party (the "source") with implicit signals derived by other players (the "observers"). Our model is motivated in part by applications in decentralized physical infrastructure networks (a.k.a. "DePIN"), an emerging application domain in which physical services (e.g., sensor information, bandwidth, or energy) are provided at least in part by untrusted and self-interested parties. A key challenge in these signal network applications is verifying the level of service that was actually provided by network participants.
We first establish a condition called source identifiability, which we show is necessary for the existence of a mechanism for which truthful signal reporting is a strict equilibrium. For a converse, we build on techniques from peer prediction to show that in every signal network that satisfies the source identifiability condition, there is in fact a strictly truthful mechanism, where truthful signal reporting gives strictly higher total expected payoff than any less informative equilibrium. We furthermore show that this truthful equilibrium is in fact the unique equilibrium of the mechanism if there is positive probability that any one observer is unconditionally honest (e.g., if an observer were run by the network owner). Also, by extending our condition to coalitions, we show that there are generally no collusion-resistant mechanisms in the settings that we consider.
We apply our framework and results to two DePIN applications: proving location, and proving bandwidth. In the location-proving setting observers learn (potentially enlarged) Euclidean distances to the source. Here, our condition has an appealing geometric interpretation, implying that the source's location can be truthfully elicited if and only if it is guaranteed to lie inside the convex hull of the observers.

Keywords

Mathematical Methods; Infrastructure; Information Infrastructure

Citation

Milionis, Jason, Jens Ernstberger, Joseph Bonneau, Scott Duke Kominers, and Tim Roughgarden. "Incentive-Compatible Recovery from Manipulated Signals, with Applications to Decentralized Physical Infrastructure." Working Paper, March 2025.
  • Read Now

About The Author

Scott Duke Kominers

Entrepreneurial Management
→More Publications

More from the Authors

    • June 2025
    • Journal of Finance

    Collusion in Brokered Markets

    By: John William Hatfield, Scott Duke Kominers and Richard Lowery
    • March 14, 2025
    • Harvard Crimson

    Harvard Students Should Ignore Calls to Boycott Israel Trek

    By: Jesse M. Fried, Paul A. Gompers, Scott Kominers and Mark C. Poznansky
    • March 2025
    • Faculty Research

    O2X: Optimizing to the X

    By: Scott Duke Kominers, Thomas Jennings and Maisie Wiltshire-Gordon
More from the Authors
  • Collusion in Brokered Markets By: John William Hatfield, Scott Duke Kominers and Richard Lowery
  • Harvard Students Should Ignore Calls to Boycott Israel Trek By: Jesse M. Fried, Paul A. Gompers, Scott Kominers and Mark C. Poznansky
  • O2X: Optimizing to the X By: Scott Duke Kominers, Thomas Jennings and Maisie Wiltshire-Gordon
ǁ
Campus Map
Harvard Business School
Soldiers Field
Boston, MA 02163
→Map & Directions
→More Contact Information
  • Make a Gift
  • Site Map
  • Jobs
  • Harvard University
  • Trademarks
  • Policies
  • Accessibility
  • Digital Accessibility
Copyright © President & Fellows of Harvard College.