Algebraic Watchdog: Mitigating Misbehavior in Wireless Network Coding

TL;DR

The paper introduces the algebraic watchdog, a novel scheme for wireless network coding that enables nodes to probabilistically detect malicious behavior and ensure secure, self-checking communication in multi-hop networks.

Contribution

It presents a new proactive detection protocol for wireless network coding that uses algebraic and graphical models to identify adversarial nodes and improve network security.

Findings

Probabilistic detection of malicious nodes is effective in two-hop and multi-hop networks.

Graphical models and algorithms like Viterbi can compute detection probabilities.

Simulation results confirm the analytical performance predictions.

Abstract

We propose a secure scheme for wireless network coding, called the algebraic watchdog. By enabling nodes to detect malicious behaviors probabilistically and use overheard messages to police their downstream neighbors locally, the algebraic watchdog delivers a secure global self-checking network. Unlike traditional Byzantine detection protocols which are receiver-based, this protocol gives the senders an active role in checking the node downstream. The key idea is inspired by Marti et al.'s watchdog-pathrater, which attempts to detect and mitigate the effects of routing misbehavior. As an initial building block of a such system, we first focus on a two-hop network. We present a graphical model to understand the inference process nodes execute to police their downstream neighbors; as well as to compute, analyze, and approximate the probabilities of misdetection and false detection. In addition, we present an algebraic analysis of the performance using an hypothesis testing framework that provides exact formulae for probabilities of false detection and misdetection. We then extend the algebraic watchdog to a more general network setting, and propose a protocol in which we can establish trust in coded systems in a distributed manner. We develop a graphical model to detect the presence of an adversarial node downstream within a general multi-hop network. The structure of the graphical model (a trellis) lends itself to well-known algorithms, such as the Viterbi algorithm, which can compute the probabilities of misdetection and false detection. We show analytically that as long as the min-cut is not dominated by the Byzantine adversaries, upstream nodes can monitor downstream neighbors and allow reliable communication with certain probability. Finally, we present simulation results that support our analysis.