Resilient Consensus for Multi-Agent Systems in the Presence of Sybil Attacks

Xiaochen Dong,Ming Xu,Yiming Wu,Ning Zheng

doi:10.3390/electronics11050800

Abstract

This paper investigates the problem of resilient consensus control for discrete-time linear multi-agent systems under Sybil attacks. We consider a node to be a Sybil node if it can generate a large number of false identities in the graph as a way of gaining disproportionate influence on the consensus performance of the network. Such attacks can easily invalidate existing resilient consensus algorithms that assume an upper bound on the number of malicious nodes in the network. To this end, we first built a new attack model based on the characteristics of the Sybil nodes. In addition, a quantized-data-based transmission scheme was developed for identifying and resisting Sybil nodes in the network. Then, an attack-resilient consensus algorithm was developed, where each normal node sends the quantitative data information with a specific label, which is generated by truncated normal distribution sampling to their neighbors. We give sufficient graphical conditions for attack models considering limited energy to ensure the consensus of linear multi-agent systems. Finally, numerical simulation examples are provided to validate the effectiveness of the proposed methods.

Highlights

In the last decade, cooperative control of multi-agent systems (MASs) has attracted significant attention from researchers and can be found in various fields [1–3], for instance, distributed computing, sensor networks, autonomous vehicles, and the Internet of Things
As one of the fundamental problems of MASs, consensus control is the combination of graph theory and control systems, which aims to make these distributed and locally cooperative agents reach an agreement in terms of some interests
The paper is organized as follows: In Section 2, we present some notions in graph theory and propose the Sybil attack model

Summary

Introduction

Cooperative control of multi-agent systems (MASs) has attracted significant attention from researchers and can be found in various fields [1–3], for instance, distributed computing, sensor networks, autonomous vehicles, and the Internet of Things. Many works have been dedicated to resilient consensus for MASs with different network situations or types of cyber-attacks [4–7]. The goal of resilient consensus is to prevent the malicious agents from influencing the system’s consensus process by appropriate consensus strategy and designing sufficient redundancy in the underlying network [8–10]. The author in [12] studied the resilient consensus problem for switched MASs. On the other hand, based on the impact of different cyber-attack characteristics on MASs, constructing corresponding control system attack models is a research hotspot [13–15]. In [5], DoS attack models in multi-agent networks are discussed, and a resilient consensus control law is given based on the static output feedback mechanism

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Conclusion