1 / 9

Voting System Properties

Explore the properties of voting systems, mixnets, and testing methodologies to optimize security and integrity. Discover the trade-offs between cryptographic and statistical soundness, and the impact of honest mixes on anonymity. Analyze open problems and potential solutions.

lluke
Download Presentation

Voting System Properties

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Voting System Properties • Most voting systems assume no collusion between more than one party for keys • Most voting systems require a consistency check by each voter for a small piece of the protocol • If 5-20% of voters check, the correctness of the entire protocol is determined by this weakest link

  2. Choosing a Mixnet • If we can trade a mixnet that requires only one honest* mix for a mixnet that is faster but requires more than one honest mix: good trade for voting • If we can trade cryptographic soundness (1-ε) for statistical soundness (99%) and speed: good trade for voting * keep permutation private from other mixes

  3. 2 Such Mixnets Assuming re-encryption: Randomized Partial Checking [JJR02] Almost Entirely Correct Mixing [BG02] Open problem 1: others? Open problem 2: throw combinatorics at BG02

  4. Mix

  5. Mix Σ Σ

  6. Necessary but not sufficient Mix Σ Σ

  7. Mix Σ ≠ Σ

  8. Properties Testing product of subsets is probabilistic: boost soundness by repeating Testing product of subsets reduces anonymity: repeating makes worst Adding additional honest mixes increases anonymity Optimize number of tests per mix and number of honest mixes to balance anonymity and soundness

  9. Open Problem 2 Analysis in paper is tricky Complexity seems to result from using random coins Idea: throw a combinatorial design at the problem Choose random instance from a family of { ? } so that guarantees can be made by anonymity sets within mixes and with adjacent honest mixes

More Related