Spam Prevention Using zk-SNARKs for Anonymous Peer-to-Peer Content Sharing Systems

TL;DR

This paper introduces a decentralized, privacy-preserving spam prevention method for peer-to-peer networks using zk-SNARKs, enabling anonymous rate-limiting without central authority or linking user submissions.

Contribution

It proposes a novel zk-SNARK-based approach for censorship-resistant, anonymous spam prevention in decentralized networks, extending from centralized to blockchain-based systems.

Findings

Effective rate-limiting under full anonymity

Decentralized implementation feasible and scalable

Enhanced censorship resistance in P2P content sharing

Abstract

Decentralized unpermissioned peer-to-peer networks are inherently vulnerable to spam when they allow arbitrary participants to submit content to a common public index or registry; preventing this is difficult due to the absence of a central arbitrator who can act as a gate-keeper. For this reason indexing of new content even in otherwise decentralized networks (e.g. Bittorrent with DHT, IPFS) has generally been left to centralized services such as torrent sites. Decentralized methods for spam prevention, such as Web of Trust, already exist[1][2] but they require submitters to assume pseudonymous identities and establish trust over time. In this paper we present a method of spam prevention that works under the assumption that the participants are fully anonymous and do not want different submissions of theirs to be linked to each other. By spam we do not specifically mean unsolicited advertising; rather it is the practice of adding a large amount of content in a short time, saturating the capacity of the network, and causing denial of service to peers. The purpose of our solution is to prevent users from saturating the system, and can be described as rate-limiting. The system should be censorship resistant: it should not be possible for submissions to be excluded because of the content itself, or for users to be excluded based on what they submit. We first discuss a solution based on a single, centralized rate-limiter that is censorship resistant and anonymous, then we extend this to a fully decentralized blockchain-based system and present methods to make it economical and scalable.