Zero-Knowledge Proof-Based Approach for Verifying the Computational Integrity of Power Grid Controls
Chin-Yao Chang, Richard Macwan, Sinnott Murphy

TL;DR
This paper proposes a zero-knowledge proof-based method to verify the computational integrity of distributed power grid controllers, enhancing security without heavy computational verification.
Contribution
It introduces a novel application of zk-STARKs to verify linear control algorithms in power grids, reducing verification complexity and increasing trustworthiness.
Findings
Derived polynomial conditions for projected linear dynamics using zk-STARKs
Demonstrated feasibility of zero-knowledge verification for power grid control algorithms
Reduced computational burden for verifiers in power system control validation
Abstract
The control of future power grids is migrating from a centralized to a distributed/decentralized scheme to enable a massive penetration of distributed energy resources and bring extreme enhancements of autonomous operations in terms of grid resilience, security, and reliability. Most effort has been on the design of distributed/decentralized controllers; however, the guarantees of the proper execution of the controls are also essential but relatively less emphasized. A common assumption is that local controllers would fully follow the designated controller dynamics based on the data received from communication channels. Such an assumption could be risky because proper execution of the controller dynamics is then built on trust in secure communication and computation. On the other hand, it is impractical for a verifier to repeat all the computations involved in the controls to verify the…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsSmart Grid Security and Resilience · Cryptography and Data Security · Blockchain Technology Applications and Security
