A verifiably secure and proportional committee election rule

The property of proportional representation in approval-based committee elections has appeared in the social choice literature for over a century, and is typically understood as avoiding the underrepresentation of minorities. However, we argue that the security of some distributed systems is directly linked to the opposite goal of avoiding the overrepresentation of any minority, a goal which leads us to an optimization objective known as Maximin Support, closely related to the axiom of Proportional Justified Representation (PJR). We provide an inapproximability result for this objective, and propose a new election rule inspired in Phragmen's methods that achieves a) a constant-factor approximation guarantee for the objective, and b) the PJR property. Furthermore, a structural property allows one to quickly verify that the winning committee satisfies the two aforementioned properties, even if the algorithm is executed by an untrusted party who only communicates the output. Finally, we present an efficient post-computation that, when paired with any approximation algorithm for Maximin Support, returns a new solution that a) preserves the approximation guarantee, b) satisfies PJR, and c) can be efficiently verified to satisfy PJR. Our work is motivated by an application on blockchains that implement Nominated Proof-of-Stake (NPoS), where the community must elect a committee of validators to participate in its consensus protocol, and where fighting overrepresentation protects the system against attacks by an adversarial minority. Our election rule enables a validator election protocol with formal and verifiable guarantees on security and proportionality. We propose a specific protocol that can be successfully implemented in spite of the stringent time constraints of a blockchain architecture, and that will be the basis for an implementation in the Polkadot network, launched in 2020.

[1]  John R. Douceur,et al.  The Sybil Attack , 2002, IPTPS.

[2]  L. Goodman,et al.  Tezos : A Self-Amending Crypto-Ledger Position Paper , 2014 .

[3]  Alfonso Cevallos,et al.  Overview of Polkadot and its Design Considerations , 2020, IACR Cryptol. ePrint Arch..

[4]  Zibin Zheng,et al.  Solutions to Scalability of Blockchain: A Survey , 2020, IEEE Access.

[5]  Dorit S. Hochbaum,et al.  About strongly polynomial time algorithms for quadratic optimization over submodular constraints , 1995, Math. Program..

[6]  Jean-François Laslier,et al.  Handbook on approval voting , 2010 .

[7]  Roman Beck,et al.  Governance in the Blockchain Economy: A Framework and Research Agenda , 2018, J. Assoc. Inf. Syst..

[8]  Joachim Gudmundsson,et al.  Computational Aspects of Multi-Winner Approval Voting , 2014, MPREF@AAAI.

[9]  Edgar R. Weippl,et al.  Agreement with Satoshi - On the Formalization of Nakamoto Consensus , 2018, IACR Cryptol. ePrint Arch..

[10]  Daniel Davis Wood,et al.  ETHEREUM: A SECURE DECENTRALISED GENERALISED TRANSACTION LEDGER , 2014 .

[11]  A. Goldberg,et al.  A new approach to the maximum-flow problem , 1988, JACM.

[12]  S. Nakamoto,et al.  Bitcoin: A Peer-to-Peer Electronic Cash System , 2008 .

[13]  Damiano Di Francesco Maesa,et al.  Blockchain 3.0 applications survey , 2020, J. Parallel Distributed Comput..

[14]  Svante Janson,et al.  Phragmén’s voting methods and justified representation , 2017, AAAI.

[15]  Svante Janson,et al.  Phragmén's and Thiele's election methods , 2016, ArXiv.

[16]  Haris Aziz,et al.  Justified representation in approval-based committee voting , 2014, Social Choice and Welfare.

[17]  Aggelos Kiayias,et al.  Reward Sharing Schemes for Stake Pools , 2018, 2020 IEEE European Symposium on Security and Privacy (EuroS&P).

[18]  Robert E. Tarjan,et al.  A Fast Parametric Maximum Flow Algorithm and Applications , 1989, SIAM J. Comput..

[19]  Edith Elkind,et al.  Proportional Justified Representation , 2016, AAAI.

[20]  Edith Elkind,et al.  On the Complexity of Extended and Proportional Justified Representation , 2018, AAAI.

[21]  David S. Johnson,et al.  Computers and Intractability: A Guide to the Theory of NP-Completeness , 1978 .

[22]  Dominik Peters,et al.  Proportionality and the Limits of Welfarism , 2020, EC.

[23]  Anamika Chauhan,et al.  Blockchain and Scalability , 2018, 2018 IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C).

[24]  Robert E. Tarjan,et al.  Improved Algorithms for Bipartite Network Flow , 1994, SIAM J. Comput..

[25]  I. Grigg EOS-An Introduction , 2017 .

[26]  Martin Lackner,et al.  Approval-Based Committee Voting: Axioms, Algorithms, and Applications , 2020, ArXiv.

[27]  Luis Sánchez-Fernández,et al.  The Maximin Support Method: An Extension of the D'Hondt Method to Approval-Based Multiwinner Elections , 2016, AAAI.

[28]  Craig Gentry,et al.  Non-interactive Verifiable Computing: Outsourcing Computation to Untrusted Workers , 2010, CRYPTO.

[29]  Leslie Lamport,et al.  Reaching Agreement in the Presence of Faults , 1980, JACM.

[30]  Piotr Faliszewski,et al.  Finding a collective set of items: From proportional multirepresentation to group recommendation , 2014, Artif. Intell..