Network Size Estimation in Small-World Networks under Byzantine Faults

TL;DR

This paper presents a distributed algorithm for estimating the size of small-world networks with many Byzantine nodes, achieving high accuracy despite adversarial interference.

Contribution

It introduces a novel randomized distributed algorithm capable of estimating network size in the presence of a large number of Byzantine nodes in small-world networks.

Findings

Estimates network size within a constant factor of log(n) with high probability.

Works in networks with up to O(n^{1 - δ}) Byzantine nodes.

Runs in O(log^3 n) rounds with small message sizes.

Abstract

We study the fundamental problem of counting the number of nodes in a sparse network (of unknown size) under the presence of a large number of Byzantine nodes. We assume the full information model where the Byzantine nodes have complete knowledge about the entire state of the network at every round (including random choices made by all the nodes), have unbounded computational power, and can deviate arbitrarily from the protocol. Our main contribution is a randomized distributed algorithm that estimates the size of a network under the presence of a large number of Byzantine nodes. In particular, our algorithm estimates the size of a sparse, "small-world", expander network with up to $O(n^{1 - \delta})$ Byzantine nodes, where $n$ is the (unknown) network size and $\delta$ can be be any arbitrarily small (but fixed) positive constant. Our algorithm outputs a (fixed) constant factor estimate of $\log(n)$ with high probability; the correct estimate of the network size will be known to a large fraction ($(1 - \epsilon)$-fraction, for any fixed positive constant $\epsilon$) of the honest nodes. Our algorithm is fully distributed, lightweight, and simple to implement, runs in $O(\log^3{n})$ rounds, and requires nodes to send and receive messages of only small-sized messages per round; any node's local computation cost per round is also small.