Detecting Active Attacks in Over-the-Air Computation using Dummy Samples

TL;DR

This paper introduces a detection scheme for active attacks in Over-the-Air computation systems, utilizing dummy samples and shared secrets to identify malicious interference with high accuracy and minimal resource overhead.

Contribution

It proposes a novel detection method leveraging dummy samples and secret subspaces to identify active attacks in OtA computation, enhancing security.

Findings

Effective attack detection with low resource cost

High detection accuracy demonstrated in simulations

Utilizes shared secret for robust detection

Abstract

Over-the-Air (OtA) computation is a newly emerged concept for computing functions of data from distributed nodes by taking advantage of the wave superposition property of wireless channels. Despite its advantage in communication efficiency, OtA computation is associated with significant security and privacy concerns that have so far not been thoroughly investigated, especially in the case of active attacks. In this paper, we propose and evaluate a detection scheme against active attacks in OtA computation systems. More explicitly, we consider an active attacker which is an external node sending random or misleading data to alter the aggregated data received by the server. To detect the presence of the attacker, in every communication period, legitimate users send some dummy samples in addition to the real data. We propose a detector design that relies on the existence of a shared secret only known by the legitimate users and the server, that can be used to hide the transmitted signal in a secret subspace. After the server projects the received vector back to the original subspace, the dummy samples can be used to detect active attacks. We show that this design achieves good detection performance for a small cost in terms of channel resources.