Prime: Byzantine Replication under Attack

Amir, Yair; Coan, Brian A.; Kirsch, John A. W.; Lane, John W.

doi:10.1109/tdsc.2010.70

Cited by 145 publications

(106 citation statements)

References 33 publications

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“…Unfortunately, as we show in this section, a Byzantine client or a Byzantine replica can attack this protocol and drastically reduce its performance. This fragility of BFT protocols is well known and motivated the development of three so-called robust protocols: Spinning [Veronese et al 2009], Prime [Amir et al 2011], and Aardvark [Clement et al 2009]. In this section, we first study the performance achieved by Aliph when clients or replicas attack the protocol (Section 6.1).…”

Section: Making Aliph Robust: R-aliphmentioning

confidence: 99%

“…The fact that efficient BFT protocols are often fragile (i.e., perform poorly under attack) motivated the development of so-called robust BFT protocols: Spinning [Veronese et al 2009], Prime [Amir et al 2011], and Aardvark [Clement et al 2009]. These protocols aim at achieving good performance when the network is synchronous, despite the presence of Byzantine faulty clients and replicas.…”

Section: A Brief Overview Of "Robust" Bft Protocolsmentioning

confidence: 99%

“…Another robust protocol that has been designed is Prime [Amir et al 2011]. In Prime, clients can send their requests to any replica in the system.…”

Section: A Brief Overview Of "Robust" Bft Protocolsmentioning

confidence: 99%

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The Next 700 BFT Protocols

Aublin

Guerraoui

Knezevic

et al. 2015

ACM Trans. Comput. Syst.

110

108

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We present Abstract (ABortable STate mAChine replicaTion), a new abstraction for designing and reconfiguring generalized replicated state machines that are, unlike traditional state machines, allowed to abort executing a client's request if "something goes wrong."Abstract can be used to considerably simplify the incremental development of efficient Byzantine faulttolerant state machine replication (BFT) protocols that are notorious for being difficult to develop. In short, we treat a BFT protocol as a composition of Abstract instances. Each instance is developed and analyzed independently and optimized for specific system conditions. We illustrate the power of Abstract through several interesting examples.We first show how Abstract can yield benefits of a state-of-the-art BFT protocol in a less painful and errorprone manner. Namely, we develop AZyzzyva, a new protocol that mimics the celebrated best-case behavior of Zyzzyva using less than 35% of the Zyzzyva code. To cover worst-case situations, our abstraction enables one to use in AZyzzyva any existing BFT protocol.We then present Aliph, a new BFT protocol that outperforms previous BFT protocols in terms of both latency (by up to 360%) and throughput (by up to 30%). Finally, we present R-Aliph, an implementation of Aliph that is robust, that is, whose performance degrades gracefully in the presence of Byzantine replicas and Byzantine clients.

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Section: Making Aliph Robust: R-aliphmentioning

confidence: 99%

Section: A Brief Overview Of "Robust" Bft Protocolsmentioning

confidence: 99%

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The Next 700 BFT Protocols

Aublin

Guerraoui

Knezevic

et al. 2015

ACM Trans. Comput. Syst.

110

108

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show abstract

“…For example, a straightforward implementation of a BFT firewall would require replicas to process every arriving message and then agree on their delivery. BFT solutions based on a leader can also become prey of an adversary, as they have a natural bottleneck replica that can be selected for the attack (instead of having to disperse the attack power over all replicas [13]). …”

Section: Design Choicesmentioning

confidence: 99%

An intrusion-tolerant firewall design for protecting SIEM systems

Garcia

Neves

Bessani

2013

2013 43rd Annual IEEE/IFIP Conference on Dependable Systems and Networks Workshop (DSN-W)

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Abstract-Nowadays, organizations are resorting to Security Information and Event Management (SIEM) systems to monitor and manage their network infrastructures. SIEMs employ a data collection capability based on many sensors placed in critical points of the network, which forwards events to a core facility for processing and support different forms of analysis (e.g., report attacks in near real time, inventory management, risk assessment). In this paper, we will focus on the defense of the core facility components by presenting a new firewall design that is resilient to very harsh failure scenarios. In particular, it tolerates not only external attacks but also the intrusion of some of its components. The firewall employs a two level filtering scheme to increase performance and to allow for some flexibility on the selection of fault-tolerance mechanisms. The first filtering stage efficiently eliminates the most common forms of attacks, while the second stage supports application rules for a more sophisticated analysis of the traffic. The fault tolerance mechanisms are based on a detection and recovery approach for the first stage, while the second stage uses state machine replication and voting.

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“…Survivability means that the SCADA system, continue to work correctly with minimal degradation performance, even if malicious anomalies have jeopardized a part of the system. To achieve survivability, the proposed system uses the anomaly tolerance method presented in [8] and [9]. In [10] Maglaras and his colleagues have offered an anomaly detection module which is able to detect malicious traffic of the network in SCADA system.…”

Section: Introductionmentioning

confidence: 99%

Anomaly detection in industrial control systems using evolutionary-based optimization of neural networks

Mansouri¹,

Majidi²,

Shamisa³

2017

Communications on Advanced Computational Science with Applicati

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Industrial control systems are increasingly used for control and monitoring of important infrastructure. Machine learning algorithms have the ability to discover patterns in large amounts of data and to create diagnosis models based on these patterns. Since modelling a large amount of unlabeled data is costly and time-consuming, the automated machine learning methods have the ability to detect anomalies in industrial control systems effectively. In this paper, first, twenty-four machine learning algorithms are evaluated for anomaly detection in gas distribution control network. Then dimensionality reduction algorithms are used to improve the accuracy of anomaly detection. Finally, by using an evolutionary based optimization for training a neural network, a new algorithm for prediction of anomalies in the SCADA system with high accuracy is proposed. The experimental results show that the proposed algorithm has the ability to detect the anomalies in the gas distribution control network with 97.5% accuracy.

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Prime: Byzantine Replication under Attack

Cited by 145 publications

References 33 publications

The Next 700 BFT Protocols

The Next 700 BFT Protocols

An intrusion-tolerant firewall design for protecting SIEM systems

Anomaly detection in industrial control systems using evolutionary-based optimization of neural networks

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