Attributed metadata history
Up to 100 retained publisher events per page for 5e1e042f52882ad27bcb2747d3f464977dc12c50f516558bf01b64831ed52d58. Withdrawals and unavailable references remain attributed to their publishers.
intelligence_src_e53adb99e40ae66258
observed · 2026-10-12 16:25:04 UTC
ePrint Report: Fair and Efficient Helper-Aided MPC with Cheater Identification Maximilian Kamps, Protik Paul, Divya Ravi Secure multi-party computation (MPC) enables privacy-preserving tasks such as auctions and voting. In practice, more than half of the parties may collude, making security against a dishonest majority desirable. Unfortunately, dishonest-majority MPC suffers from high communication and can achieve only abort security. For instance, in an auction, an adversary may abort after learning the outcome and rerun the protocol with a higher bid. Helper-aided MPC mitigates these limitations by introducing a semi-honest, non-colluding helper, a model that naturally fits settings with a central governing or coordinating entity and provides strong guarantees even when up to $n-1$ parties are malicious. The model assumes that the adversary can either semi-honestly corrupt the helper or maliciously corrupt up to $n-1$ parties (excluding the helper). While existing helper-aided protocols are fair i.e. either all parties receive the output or none do; they still allow the adversary to abort without any pe
Fingerprint: 7213709407b81bea40ded360a425156646d3e7bf8b5745323db9356152f9cae4
intelligence_src_e53adb99e40ae66258
observed · 2026-10-12 16:25:03 UTC
available
Fingerprint: 366cb966e32414edc1db353849a1ee8d6b8462b83786e04001881ba6594765ad