Tempora-Fusion: Time-Lock Puzzle with Efficient Verifiable Homomorphic Linear Combination
Aydin Abadi

TL;DR
Tempora-Fusion introduces a novel time-lock puzzle scheme enabling efficient homomorphic linear combinations of puzzles from multiple clients, with built-in verification of computation correctness, applicable to secure timed computations in various domains.
Contribution
It presents the first homomorphic TLP supporting verifiable linear combinations without asymmetric cryptography, enhancing efficiency and security in timed computations.
Findings
Supports verification of computation correctness.
Avoids asymmetric cryptography for verification.
Applicable to federated learning, online banking, e-voting.
Abstract
To securely transmit sensitive information into the future, Time-Lock Puzzles (TLPs) have been developed. Their applications include scheduled payments, timed commitments, e-voting, and sealed-bid auctions. Homomorphic TLP is a key variant of TLP that enables computation on puzzles from different clients. This allows a solver/server to tackle only a single puzzle encoding the computation's result. However, existing homomorphic TLPs lack support for verifying the correctness of the computation results. We address this limitation by introducing Tempora-Fusion, a TLP that allows a server to perform homomorphic linear combinations of puzzles from different clients while ensuring verification of computation correctness. This scheme avoids asymmetric-key cryptography for verification, thus paving the way for efficient implementations. We discuss our scheme's application in various domains,…
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
TopicsVideo Analysis and Summarization · Multimedia Communication and Technology · Artificial Intelligence in Games
