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, such as federated learning, scheduled payments in online banking, and e-voting.

翻译：为了安全地将敏感信息传输至未来，时间锁谜题（TLP）应运而生。其应用场景包括定时支付、定时承诺、电子投票和密封投标拍卖等。同态时间锁谜题是TLP的一种关键变体，它支持对不同客户端的谜题进行计算。这使得求解器/服务器只需处理编码了计算结果的单个谜题。然而，现有的同态TLP缺乏对计算结果正确性验证的支持。针对这一局限，我们提出了Tempora-Fusion，这是一种允许服务器对不同客户端的谜题执行同态线性组合，同时确保计算正确性可验证的TLP。该方案避免了使用非对称密钥密码学进行验证，从而为高效实现铺平了道路。我们探讨了该方案在联邦学习、在线银行定时支付及电子投票等多个领域的应用前景。