Swarm attack: A self-organized model to recover from malicious communication manipulation in a swarm of simple simulated agents

Giuseppe Primiero*, Elio Tuci, Jacopo Tagliabue, Eliseo Ferrante

*Corresponding author for this work

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Abstract

Non-centralised behaviour such as those that characterise swarm robotics systems are vulnerable to intentional disruptions from internal or external adversarial sources. Threats in the context of swarm robotics can be executed through goal, behaviour, environment or communication manipulation. Experimental studies in this area are still sparse. We study an attack scenario performed by actively modifying the data between authorised participants. We formulate a robust probabilistic adaptive defence mechanism which does not aim at identifying malicious agents, but to provide the swarm with the means to minimise the consequences of the attack. The mechanism relies on a dynamic modification of the probability of agents to change their current information in view of new contradictory or corroborating incoming data. We investigate several experimental conditions in simulation. The results show that the presence of adversaries in the swarm hinders reaching consensus to the majority opinion when using a baseline method, but that there are several conditions in which our adaptive defence mechanism is highly efficient.

Original languageEnglish
Title of host publicationSwarm Intelligence - 11th International Conference, ANTS 2018, Proceedings
EditorsAndreagiovanni Reina, Anders L. Christensen, Vito Trianni, Christian Blum, Marco Dorigo, Mauro Birattari
PublisherSpringer Verlag
Pages213-224
Number of pages12
ISBN (Print)9783030005320
DOIs
Publication statusPublished - 1 Jan 2018
Externally publishedYes
Event11th International Conference on Swarm Intelligence, ANTS 2018 - Rome, Italy
Duration: 29 Oct 201831 Oct 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11172 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference11th International Conference on Swarm Intelligence, ANTS 2018
CountryItaly
CityRome
Period29/10/1831/10/18

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