Killer | Privacy and Verifiability in Decentralized Electronic Voting Systems | Buch | 978-3-8440-9257-8 | sack.de

Buch, Englisch, 334 Seiten, Format (B × H): 148 mm x 210 mm, Gewicht: 519 g

Reihe: Berichte aus der Informatik

Killer

Privacy and Verifiability in Decentralized Electronic Voting Systems


1. Auflage 2023
ISBN: 978-3-8440-9257-8
Verlag: Shaker

Buch, Englisch, 334 Seiten, Format (B × H): 148 mm x 210 mm, Gewicht: 519 g

Reihe: Berichte aus der Informatik

ISBN: 978-3-8440-9257-8
Verlag: Shaker


Fair and secure voting is a cornerstone of democracies and, at the same time, one of the most challenging government processes. Thus, government services are increasingly digitized, and an essential effort is digitizing democratic processes, such as deploying Electronic Voting (EV) systems. A key difference and crucial aspect of voting processes is whether votes are cast in person or remotely (e.g., via the internet), i.e., Remote EV (REV) systems allow voters to remotely cast their ballot from an uncontrolled environment. Transparency is critical for voting systems and especially crucial in achieving verifiability properties. Thus, Blockchains (BC) and Distributed Ledgers (DL) emerged prominently as an instantiation of the PBB in voting systems' architectures. While permissionless consensus is beneficial for many use-cases, such trust assumptions do not align with voting systems used in democratic elections, where a minimal set of reliable and trustworthy authorities is established beforehand. Based on permissioned DLs, this thesis proposes (1) Proverum, a novel identity management approaches for the Swiss Remote Postal Voting (RPV) system, as well as (2) Helverify, an End-to-End Verifiable (E2E-V) RPV system. Besides these systems strengthening the Swiss RPV, three REV systems are introduced, a fully decentralized voting system based on Homomorphic Encryption (HE) that achieves Receipt-Freeness and E2E-V, and fourth, its successors based on Re-Encryption Mixnets. Finally, a decentralized voting system achieving Unconditional Privacy is introduced, i.e., its privacy guarantees do not depend on any computational hardness assumptions. This thesis contains novel RPV and REV systems, which are evaluated quantitatively and qualitatively.

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