Markov Chains Competing for Transitions: Application to Large-Scale Distributed Systems

International audienceWe consider the behavior of a stochastic system composed of several identically distributed, but non independent, discrete-time absorbing Markov chains competing at each instant for a transition. The competition consists in determining at each instant, using a given probability distribution, the only Markov chain allowed to make a transition. We analyze the first time at which one of the Markov chains reaches its absorbing state. We obtain its distribution and its expectation and we propose an algorithm to compute these quantities. We also exhibit the asymptotic behavior of the system when the number of Markov chains goes to infinity. Actually, this problem comes from the analysis of large-scale distributed systems and we show how our results apply to this domain

PeerCube: an Hypercube-based P2P Overlay Robust against Collusion and Churn

International audienceIn this paper we present PeerCube, a DHT-based system that aims at minimizing performance penalties caused by high churn while preventing malicious peers from subverting the system through collusion. This is achieved by i) applying a clustering strategy to support quorum-based operations; ii) using a randomised insertion algorithm to reduce the probability with which colluding Byzantine peers corrupt clusters, and; iii) leveraging on the properties of PeerCube's hypercube structure to allow operations to be successfully handled despite the corruption of some clusters. Despite a powerful adversary that can inspect the whole system and issue malicious join requests as often as it wishes, PeerCube guarantees robust operations in O(logN) messages, with N the number of peers in the system. Extended simulations validate PeerCube robustness

Modélisation et Évaluation des Attaques Ciblées dans un Overlay Structuré

Session Sécurité RéseauInternational audienceDans cet article, nous nous intéressons aux attaques ciblées dans le cadre des systèmes pair-à-pair large échelle. Ces attaques ont pour but d'affaiblir les nœuds ciblés de manière à diminuer leur capacité à fournir ou à utiliser des services de l'overlay. Pour se prémunir de telles attaques, nous tirons parti du clustering de l'overlay sous-jacent. Cela permet de mettre en place un système de churn induit préservant la répartition aléatoire des identifiants des nœuds dans l'overlay et ainsi rendre impossible toute prédiction de l'adversaire quant à celle-ci. Nous montrons qu'en randomisant légèrement les opérations élémentaires de l'overlay, ainsi qu'en introduisant des temps de séjour adaptés, l'effet de ces attaques ciblées est sensiblement amoindri, et la propagation des effets de l'attaque à l'ensemble du système est évitée

Dependability Evaluation of Cluster-based Distributed Systems

19International audienceAwerbuch and Scheideler have shown that peer-to-peer overlay networks can survive Byzantine attacks only if malicious nodes are not able to predict what will be the topology of the network for a given sequence of join and leave operations. In this paper we inves- tigate adversarial strategies by following speci c protocols. Our analysis demonstrates rst that an adversary can very quickly subvert overlays based on distributed hash tables by simply never triggering leave operations. We then show that when all nodes (honest and malicious ones) are imposed on a limited lifetime, the system eventually reaches a stationary regime where the ratio of polluted clusters is bounded, independently from the initial amount of corruption in the system

Analytic Study of the Impact of Churn in Cluster-Based Structured P2P Overlays

International audienceIn this paper we present an analytic study of the impact of churn in cluster-based overlay networks. Cluster-based overlays keep the best of unstructured and structured overlays in terms of scalability, fault-tolerance and stability. Most of join and leave events have no impact on the overall overlay topology making these overlays highly robust to high churn. The only situations that effectively give rise to topology modifications are when clusters need to split because they exceed some maximal size or need to merge because they fall under some minimal size. Although these operations are scalable, they are intricate in the sense that they need synchronization among nodes involved in these operations. In this paper we accurately predict the frequency at which the topology of the overlay changes according to the number of join/leave operations. Our analysis improves upon existing studies by showing that these relevant topological changes are very infrequent, namely $\Theta(N)$ join/leave events are required before any of these topological operations occur, where $N$ is the number of peers currently in the system. Such a result clearly demonstrates the appropriateness of these overlays to high churn

Relying on Consensus does not Make Bitcoin Safer

International audienceSeveral distributed cryptocurrencies systems have emerged, and among them, Bitcoin is often designated as the pioneer this kind of systems. As such, Bitcoin shows some vulnerabil- ities in presence of malicious entities, and some recent works have proposed to improve upon Bitcoin weaknesses. This brief abstract is devoted to the analysis of one of these recent works, and shows through an analytical performance evaluation that new Bitcoin improvements are still needed

Brief Announcement: Induced Churn to Face Adversarial Behavior in Peer-to-Peer Systems

International audienceAwerbuch and Scheideler have shown that peer-to-peer overlays networks can only survive Byzantine attacks if malicious nodes are not able to predict what will be the topology of the network for a given sequence of join and leave operations. A prerequisite for this condition to hold is to guarantee that nodes identifiers randomness is continuously preserved. However targeted join/leave attacks may quickly endanger the relevance of such an assumption. Inducing churn has been shown to be the other fundamental ingredient to preserve randomness. Several strategies based on these principles have been proposed. Most of them are based on locally induced churn. However either they have been proven incorrect or they involve a too high level of complexity to be practically acceptable. The other ones, based on globally induced churn, enforce limited lifetime for each node in the system. However, these solutions keep the system in an unnecessary hyper-activity, and thus need to impose strict restrictions on nodes joining rate which clearly limit their applicability to open systems. In this paper we propose to leverage the power of clustering to design a provably correct and practically usable solution that preserves randomness under a bounded adversary

A Self-organising Isolated Anomaly Detection Architecture for Large Scale Systems

International audienceMonitoring a system is the ability of collecting and analyzing relevant information provided by the monitored devices so as to be continuously aware of the system state. However, the ever growing complexity and scale of systems makes both real time monitoring and fault detection a quite tedious task. Thus the usually adopted option is to focus solely on a subset of information states, so as to provide coarse-grained indicators. As a consequence, detecting isolated failures or anomalies is a quite challenging issue. In this work, we propose to address this issue by pushing the monitoring task at the edge of the network. We present a peer-to-peer based architecture, which enables nodes to adaptively and efficiently self-organize according to their ''health'' indicators. By exploiting both temporal and spatial correlations that exist between a device and its vicinity, our approach guarantees that only isolated anomalies (an anomaly is isolated if it impacts solely a monitored device) are reported on the fly to the network operator. We show that the end-to-end detection process, i.e., from the local detection to the management operator reporting, requires a logarithmic number of messages in the size of the network

Sycomore : un registre de transactions distribué et public au débit auto-adaptatif

International audienceBitcoin est un système pair-à-pair de crypto-devises considéré comme l’un des pionniers de ce type de système. Lablockchain, une structure de donnée particulière, est la clé de voûte de ce système. Celle-ci est mise à jour régulièrementpar l’ajout d’une nouvelle séquence de transactions. La fréquence des mises à jour constante, couplée à une bornemaximale sur les transactions incluses dans celles-ci induit un débit d’enregistrement maximal borné. Cette limite,relativement basse, est l’un des freins à l’essor de Bitcoin. Cet article présente une structure de données alternativeorientée graphe permettant de s’adapter dynamiquement au besoin d’enregistrement de transactions

PeerCube: an Hypercube-based P2P Overlay Robust against Collusion and Churn

In this paper we present PeerCube, a DHT-based system that aims at minimizing performance penalties caused by high churn while preventing malicious peers from subverting the system through collusion. This is achieved by i) applying a clustering strategy to support quorum-based operations; ii) using a randomised insertion algorithm to reduce the probability with which colluding Byzantine peers corrupt clusters, and; iii) leveraging on the properties of PeerCube's hypercube structure to allow operations to be successfully handled despite the corruption of some clusters. Despite a powerful adversary that can inspect the whole system and issue malicious join requests as often as it wishes, PeerCube guarantees robust operations in O(logN) messages, with N the number of peers in the system. Extended simulations validate PeerCube robustness