Approximate Agreement under Mobile Byzantine Faults

Bonomi, Silvia; Pozzo, Antonella Del; Potop-Butucaru, Maria; Tixeuil, Sébastien

doi:10.1016/j.tcs.2018.08.001

Cited by 26 publications

(28 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This proposition can be seen as an extension of a result given in [4], which deals with the Byzantine-type mobile adversary model. The condition there is n ≥ 3 f + 1.…”

Section: Proof Of Proposition 31mentioning

confidence: 58%

“…This is intuitive since Byzantine adversaries are more powerful. The proof technique in [4] is to transform the problem so that a general result in [17] for static adversaries can be applied. For Proposition 3.1, we have proved using arguments similar to those in [9], [19], which are also for the static case.…”

Section: Proof Of Proposition 31mentioning

confidence: 99%

“…These models are different in terms of the timings of attacks for the adversaries and the capabilities of the agents recovering from attacks or infections. Recently, by [4], [28], [30], these studies have been extended to the case where the agents' states take real values. However, we must note that all of these studies are limited in two aspects: One is that the networks are assumed to take complete graph forms; such networks are very dense and require resources for communications.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Resilient Consensus Against Mobile Malicious Agents

Wang

Ishii

Bonnet

et al. 2020

Preprint

View full text Add to dashboard Cite

This paper addresses novel consensus problems in the presence of adversaries that can move within the network and induce faulty behaviors in the attacked agents. By adopting several mobile adversary models from the computer science literature, we develop protocols which can mitigate the influence of such malicious agents. The algorithms follow the class of mean subsequence reduced (MSR) algorithms, under which agents ignore the suspicious values received from neighbors during their state updates. Different from the static adversary models, even after the adversaries move away, the infected agents may remain faulty in their values, whose effects must be taken into account. We develop conditions on the network structures for both the complete and non-complete graph cases, under which the proposed algorithms are guaranteed to attain resilient consensus. Extensive simulations are carried out over random graphs to verify the effectiveness of our approach under uncertainties in the systems.

show abstract

“…This proposition can be seen as an extension of a result given in [4], which deals with the Byzantine-type mobile adversary model. The condition there is n ≥ 3 f + 1.…”

Section: Proof Of Proposition 31mentioning

confidence: 58%

Section: Proof Of Proposition 31mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Resilient Consensus Against Mobile Malicious Agents

Wang

Ishii

Bonnet

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…Table 2 Differences between Schemes 1 and 2. in Table 1. In computer science (Bonomi et al (2019); LeBlanc et al (2013); Lynch (1996)), a common limitation is that MSR-based algorithms have the maximum tolerable number of malicious nodes n ≥ 2f + 1 only for complete graphs. In comparison, it is clear that the proposed Schemes 1 and 2 can tolerate more adversaries.…”

Section: Discussionmentioning

confidence: 99%

Secure consensus with distributed detection via two-hop communication

Yuan

Ishii

2021

Automatica

View full text Add to dashboard Cite

“…For example, Gallet et al [11] examine a system that can allocate the same identifier to multiple nodes. In [5], [18], [8], the authors examine a synchronous system with mobile Byzantine faults -those which hop from one node to another across rounds. In [23], [24], the authors consider self-stabilizing agreement problems in the presence of Byzantine faults, i.e., the correct nodes have to recover from arbitrary initial state even when the other Byzantine nodes maliciously prevent the correct nodes from recovering.…”

Section: Related Workmentioning

confidence: 99%

Brief Announcement: Byzantine Agreement with Unknown Participants and Failures

Khanchandani

Wattenhofer

2020

Proceedings of the 39th Symposium on Principles of Distributed Computing

View full text Add to dashboard Cite

A set of mutually distrusting participants that want to agree on a common opinion must solve an instance of a Byzantine agreement problem. These problems have been extensively studied in the literature. However, most of the existing solutions assume that the participants are aware of n-the total number of participants in the system-and fan upper bound on the number of Byzantine participants. In this paper, we show that most of the fundamental agreement problems can be solved without affecting resiliency even if the participants do not know the values of (possibly changing) n and f. Specifically, we consider a synchronous system where the participants have unique but not necessarily consecutive identifiers, and give Byzantine agreement algorithms for reliable broadcast, approximate agreement, rotorcoordinator, early terminating consensus and total ordering in static and dynamic systems, all with the optimal resiliency of n > 3f. Moreover, we show that synchrony is necessary as an agreement with probabilistic termination is impossible in a semi-synchronous or asynchronous system if the participants are unaware of n and f .

show abstract

Approximate Agreement under Mobile Byzantine Faults

Cited by 26 publications

References 10 publications

Resilient Consensus Against Mobile Malicious Agents

Resilient Consensus Against Mobile Malicious Agents

Secure consensus with distributed detection via two-hop communication

Brief Announcement: Byzantine Agreement with Unknown Participants and Failures

Contact Info

Product

Resources

About