Swarm Attack: A Self-organized Model to Recover from Malicious Communication Manipulation in a Swarm of Simple Simulated Agents

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

doi:10.1007/978-3-030-00533-7_17

Cited by 11 publications

(7 citation statements)

References 18 publications

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“…Compared to the latest works in swarms (Canciani et al, 2019;Maître et al, 2020;Prasetyo et al, 2019;Primiero et al, 2018), to the best of our knowledge, in this paper we study for the first time the interplay between different option quality, zealot quantity and proportion of informed agents, by extending the preliminary studies in Prasetyo et al (2020) and , in which either all agents or none of the agents were able to measure the quality of their opinion and disseminate differentially based on that. In particular, we introduce here the explicit distinction between informed and uninformed agents, and study for the first time the case in which these two types of agents co-exist in the swarm at the same time.…”

Section: Related Workmentioning

confidence: 93%

Robot swarm democracy: the importance of informed individuals against zealots

et al. 2021

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In this paper we study a generalized case of best-of-n model, which considers three kind of agents: zealots, individuals who remain stubborn and do not change their opinion; informed agents, individuals that can change their opinion, are able to assess the quality of the different options; and uninformed agents, individuals that can change their opinion but are not able to assess the quality of the different opinions. We study the consensus in different regimes: we vary the quality of the options, the percentage of zealots and the percentage of informed versus uninformed agents. We also consider two decision mechanisms: the voter and majority rule. We study this problem using numerical simulations and mathematical models, and we validate our findings on physical kilobot experiments. We find that (1) if the number of zealots for the lowest quality option is not too high, the decision-making process is driven toward the highest quality option; (2) this effect can be improved increasing the number of informed agents that can counteract the effect of adverse zealots; (3) when the two options have very similar qualities, in order to keep high consensus to the best quality it is necessary to have higher proportions of informed agents.

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Section: Related Workmentioning

confidence: 93%

Robot swarm democracy: the importance of informed individuals against zealots

et al. 2021

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“…Sargeant and Tomlinson ( 2016 ) study a wider range of attacker strategies, such as eavesdropping, data manipulation, and denial of service in robot swarms. Primiero et al ( 2018 ) show that the propagation of deceitful information through the swarm can be prevented if robots probabilistically change their belief.…”

Section: Related Workmentioning

confidence: 99%

Blockchain Technology Secures Robot Swarms: A Comparison of Consensus Protocols and Their Resilience to Byzantine Robots

2020

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Consensus achievement is a crucial capability for robot swarms, for example, for path selection, spatial aggregation, or collective sensing. However, the presence of malfunctioning and malicious robots (Byzantine robots) can make it impossible to achieve consensus using classical consensus protocols. In this work, we show how a swarm of robots can achieve consensus even in the presence of Byzantine robots by exploiting blockchain technology. Bitcoin and later blockchain frameworks, such as Ethereum, have revolutionized financial transactions. These frameworks are based on decentralized databases (blockchains) that can achieve secure consensus in peer-to-peer networks. We illustrate our approach in a collective sensing scenario where robots in a swarm are controlled via blockchain-based smart contracts (decentralized protocols executed via blockchain technology) that serve as “meta-controllers” and we compare it to state-of-the-art consensus protocols using a robot swarm simulator. Additionally, we show that our blockchain-based approach can prevent attacks where robots forge a large number of identities (Sybil attacks). The developed robot-blockchain interface is released as open-source software in order to facilitate future research in blockchain-controlled robot swarms. Besides increasing security, we expect the presented approach to be important for data analysis, digital forensics, and robot-to-robot financial transactions in robot swarms.

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“…They performed a preliminary study on their effect on the best-of-n with four mechanisms: voter, majority, cross inhibition, and k-unanimity (q-voter). In [22], the authors also looked at the effects of malicious adversarial zealots in a data communication manipulation scenario, proposing a probabilistic decision-making rule to increase resilience. A very recent extension has been applied and evaluated the same scheme to a simulated swarm robotics scenario [14].…”

Section: State Of the Artmentioning

confidence: 99%

Zealots Attack and the Revenge of the Commons: Quality vs Quantity in the Best-of-n

Masi

Prasetyo

Tuci

et al. 2020

Lecture Notes in Computer Science

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Swarm Attack: A Self-organized Model to Recover from Malicious Communication Manipulation in a Swarm of Simple Simulated Agents

Cited by 11 publications

References 18 publications

Robot swarm democracy: the importance of informed individuals against zealots

Robot swarm democracy: the importance of informed individuals against zealots

Blockchain Technology Secures Robot Swarms: A Comparison of Consensus Protocols and Their Resilience to Byzantine Robots

Zealots Attack and the Revenge of the Commons: Quality vs Quantity in the Best-of-n

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