Brahms: Byzantine resilient random membership sampling

Bortnikov, Edward; Gurevich, Maxim; Keidar, Idit; Kliot, Gabriel; Shraer, Alexander

doi:10.1016/j.comnet.2009.03.008

Cited by 83 publications

(119 citation statements)

References 42 publications

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“…This is achieved by using full membership (i.e., the nodes know the list of all other nodes in the system) or a random peer sampling protocol, e.g., [33,27]. Such sampling protocols can be made robust to byzantine attacks by using techniques such as Brahms [6]. Indeed, a node might be tempted to tamper with the peer sampling service in order to be chosen, and thus served content, more frequently by other nodes.…”

Section: Model and Gossip Protocolmentioning

confidence: 99%

Tracking freeriders in gossip-based content dissemination systems

et al. 2014

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a b s t r a c tGossip-based protocols have proven very efficient for disseminating high-bandwidth content such as video streams in a peer-to-peer fashion. However, for the protocols to work, nodes are required to collaborate by devoting a fraction of their upload bandwidth, a scarce resource for some of them, to forward the content they receive to other nodes. Consequently, such protocols suffer from freeriding, a common phenomenon on the Internet, which consists in selfishly benefiting from the system without contributing its fair share. Due to the dynamic nature and the inherent randomness of gossip protocols and to the high scalability requirements of video streaming systems, detecting freeriders is a difficult challenge.This paper presents LiFTinG, the first protocol for detecting freeriders, including colluding ones, in gossip-based content dissemination systems with asymmetric data exchanges. In addition, LiFTinG is still able to detect freeriders when network coding, a widely used technique to improve the efficiency of content dissemination, is used. LiFTinG relies on nodes to track abnormal behavior by cross-checking the history of their previous interactions and exploits the fact that nodes pick neighbors at random to prevent colluding nodes from mutually covering up their bad actions.We present a methodology for setting the parameters of LiFTinG to their optimal value, based on a theoretical analysis and we quantify theoretically the performance of LiFTinG. We derive, based on simulations, the optimal strategy of freeriders by taking into account, through a utility function, the benefit of freeriding and the probability of being detected. In addition to these simulations, we report on the deployment of LiFTinG on PlanetLab. In a 300-node system, where a stream of 674 kbps is broadcasted, LiFTinG incurs a maximum Contents lists available at ScienceDirectComputer Networks j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / c o m n e t overhead of only 8% and provides good detection results: For instance, with 10% of freeriders decreasing their contribution by up to 30%, LiFTinG detects 86% of the freeriders after only 30 s and wrongfully expels only a few honest nodes (most of them actually being buggy).

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Section: Model and Gossip Protocolmentioning

confidence: 99%

Tracking freeriders in gossip-based content dissemination systems

et al. 2014

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“…Brahms [71], the Secure Peer Sampling [72], and PuppetCast [73] are three examples of PSS protocols that take into account the presence of byzantine nodes wishing to bias the sampling.…”

Section: Gossip-based Networking and Security Aspectsmentioning

confidence: 99%

Gossip-Based Networking for Internet-Scale Distributed Systems

Rivière

Voulgaris

2011

Lecture Notes in Business Information Processing

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Abstract. In the era of Internet-scale applications, an increasing number of services are distributed over pools of thousands to millions of networked computers. Along with the obvious advantages in performance and capacity, such a massive scale comes also with challenges. Continuous changes in the system become the norm rather than the exception, either because of inevitable hardware failures or merely due to standard maintenance and upgrading procedures. Rather than trying to impose rigid control on the massive pools of resources, we should equip Internet-scale applications with enough flexibility to work around inevitable faults. In that front, gossiping protocols have emerged as a promising component due to their highly desirable properties: self-healing, self-organizing, symmetric, immensely scalable, and simple. Through visiting a representative set of fundamental gossiping protocols, this paper provides insight on the principles that govern their behavior. By focusing on the rationale and incentives behind gossiping protocols, we introduce the reader to the alternative way of managing massive scale systems through gossiping, and we intrigue her or his interest to delve deeper into the subject by providing an extensive list of pointers.

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“…Fireflies [17], for instance, builds a randomized intrusion-tolerant overlay on which Byzantine nodes have only a limited control, and is resilient to the eclipse attack (i.e., no node has only Byzantine neighbors [36]). Brahms [3] provides unbiased uniform random peer-sampling in the presence of Byzantine nodes. Finally, AVMON [23] builds a pseudo-random overlay based on the hashes of the nodes' IP addresses (on which malicious nodes have very little, if any, control) thus reducing the , and has proxies of its own in the successive group g i+1 .…”

Section: System Modelmentioning

confidence: 99%

Decentralized Polling with Respectable Participants

Guerraoui

Huguenin

Kermarrec

et al. 2009

Lecture Notes in Computer Science

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a b s t r a c tWe consider the polling problem in a social network: participants express support for a given option and expect an outcome reflecting the opinion of the majority. Individuals in a social network care about their reputation: they do not want their vote to be disclosed or any potential misbehavior to be publicly exposed. We exploit this social aspect of users to model dishonest behavior, and show that a simple secret sharing scheme, combined with lightweight verification procedures, enables private and accurate polling without requiring any central authority or cryptography.We present DPol, a simple and scalable distributed polling protocol in which misbehaving nodes are exposed with positive probability and in which the probability of honest participants having their privacy violated is traded off against the impact of dishonest participants on the accuracy of the polling result. The trade-off is captured by a generic parameter of the protocol, an integer k called the privacy parameter. In a system of N nodes with B dishonest participants, the probability of disclosing a participant's vote is bounded by (B/N) k+1 , whereas the impact on the score of each polling option is at most (3k + 2)B, with high probability when dishonest users are a minority (i.e., B < N/2), assuming nodes are uniformly spread across groups used by the system. When dishonest users are few (i.e., B < √ N), the impact bound holds deterministically and our protocol is asymptotically accurate: there is negligible difference between the true result score of the poll and the outcome of our protocol.To demonstrate the practicality of DPol, we report on its deployment on 400 PlanetLab nodes. The relative error of the polling result is less than 10% when faced with the message loss, crashes and delays inherent in PlanetLab. Our experiments show that the impact on the score of each polling option by dishonest nodes is (2k + 1)B on average, consistently lower that the theoretical bound of (3k + 2)B.

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Brahms: Byzantine resilient random membership sampling

Cited by 83 publications

References 42 publications

Tracking freeriders in gossip-based content dissemination systems

Tracking freeriders in gossip-based content dissemination systems

Gossip-Based Networking for Internet-Scale Distributed Systems

Decentralized Polling with Respectable Participants

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