Signature-Free Asynchronous Binary Byzantine Consensus with t<<n/3, O(n²) Messages, and O(1) Expected Time

International audienceThis paper is on broadcast and agreement in asynchronous message-passing systems made up of n processes, and where up to t processes may have a Byzantine Behavior. Its first contribution is a powerful , yet simple, all-to-all broadcast communication abstraction suited to binary values. This abstraction, which copes with up to t < n/3 Byzantine processes, allows each process to broadcast a binary value, and obtain a set of values such that (1) no value broadcast only by Byzantine processes can belong to the set of a correct process, and (2) if the set obtained by a correct process contains a single value v, then the set obtained by any correct process contains v. The second contribution of the paper is a new round-based asynchronous consensus algorithm that copes with up to t < n/3 Byzantine processes. This algorithm is based on the previous binary broadcast abstraction and a weak common coin. In addition of being signature-free and optimal with respect to the value of t, this consensus algorithm has several noteworthy properties: the expected number of rounds to decide is constant; each round is composed of a constant number of communication steps and involves O(n²) messages; each message is composed of a round number plus a constant number of bits. Moreover , the algorithm tolerates message reordering by the adversary (i.e., the Byzantine processes)

How to securely replicate services (preliminary version)

A method is presented for constructing replicated services that retain their availability and integrity despite several servers and clients being corrupted by an intruder, in addition to others failing benignly. More precisely, a service is replicated by 'n' servers in such a way that a correct client will accept a correct server's response if, for some prespecified parameter, k, at least k servers are correct and fewer than k servers are correct. The issue of maintaining causality among client requests is also addressed. A security breach resulting from an intruder's ability to effect a violation of causality in the sequence of requests processed by the service is illustrated. An approach to counter this problem is proposed that requires that fewer than k servers are corrupt and, to ensure liveness, that k is less than or = n - 2t, where t is the assumed maximum total number of both corruptions and benign failures suffered by servers in any system run. An important and novel feature of these schemes is that the client need not be able to identify or authenticate even a single server. Instead, the client is required only to possess at most two public keys for the service

Fast Agreement in Networks with Byzantine Nodes

We study Consensus in synchronous networks with arbitrary connected topologies. Nodes may be faulty, in the sense of either Byzantine or proneness to crashing. Let t denote a known upper bound on the number of faulty nodes, and D_s denote a maximum diameter of a network obtained by removing up to s nodes, assuming the network is (s+1)-connected. We give an algorithm for Consensus running in time t + D_{2t} with nodes subject to Byzantine faults. We show that, for any algorithm solving Consensus for Byzantine nodes, there is a network G and an execution of the algorithm on this network that takes ?(t + D_{2t}) rounds. We give an algorithm solving Consensus in t + D_{t} communication rounds with Byzantine nodes using authenticated messages of polynomial size. We show that for any numbers t and d > 4, there exists a network G and an algorithm solving Consensus with Byzantine nodes using authenticated messages in fewer than t + 3 rounds on G, but all algorithms solving Consensus without message authentication require at least t + d rounds on G. This separates Consensus with Byzantine nodes from Consensus with Byzantine nodes using message authentication, with respect to asymptotic time performance in networks of arbitrary connected topologies, which is unlike complete networks. Let f denote the number of failures actually occurring in an execution and unknown to the nodes. We develop an algorithm solving Consensus against crash failures and running in time ?(f + D_{f}), assuming only that nodes know their names and can differentiate among ports; this algorithm is also communication-efficient, by using messages of size ?(mlog n), where n is the number of nodes and m is the number of edges. We give a lower bound t+D_t-2 on the running time of any deterministic solution to Consensus in (t+1)-connected networks, if t nodes may crash

Asynchronous Local Computations in Distributed Bayesian Learning

Due to the expanding scope of machine learning (ML) to the fields of sensor networking, cooperative robotics and many other multi-agent systems, distributed deployment of inference algorithms has received a lot of attention. These algorithms involve collaboratively learning unknown parameters from dispersed data collected by multiple agents. There are two competing aspects in such algorithms, namely, intra-agent computation and inter-agent communication. Traditionally, algorithms are designed to perform both synchronously. However, certain circumstances need frugal use of communication channels as they are either unreliable, time-consuming, or resource-expensive. In this paper, we propose gossip-based asynchronous communication to leverage fast computations and reduce communication overhead simultaneously. We analyze the effects of multiple (local) intra-agent computations by the active agents between successive inter-agent communications. For local computations, Bayesian sampling via unadjusted Langevin algorithm (ULA) MCMC is utilized. The communication is assumed to be over a connected graph (e.g., as in decentralized learning), however, the results can be extended to coordinated communication where there is a central server (e.g., federated learning). We theoretically quantify the convergence rates in the process. To demonstrate the efficacy of the proposed algorithm, we present simulations on a toy problem as well as on real world data sets to train ML models to perform classification tasks. We observe faster initial convergence and improved performance accuracy, especially in the low data range. We achieve on average 78% and over 90% classification accuracy respectively on the Gamma Telescope and mHealth data sets from the UCI ML repository

Optimal mobile byzantine fault tolerant distributed storage: [Extended Abstract]

We present an optimal emulation of a server based regular read/write storage in a synchronous round-free messagepassing system that is subject to mobile Byzantine failures and prove that the problem is impossible to solve in asynchronous settings. In a system with n servers implementing a regular register, our construction tolerates faults (or attacks) that can be abstracted by agents that are moved (in an arbitrary and unforeseen manner) by a computationally unbounded adversary from a server to another in order to deviate the server's computation. When a server is infected by an adversarial agent, it behaves arbitrarily until the adversary decides to "move" the agent to another server. We investigate the case where the movements of the mobile Byzantine agents are decided by the adversary and are completely decoupled from the message communication delay. Our emulation spans two awareness models: servers with and without self-diagnosis mechanism. In the first case servers are aware that the mobile Byzantine agent has left and hence they can stop running the protocol until they recover a correct state while in the second case, servers are not aware of their faulty state and continue to run the protocol using an incorrect local state. Our results, proven optimal with respect to the threshold of the tolerated mobile Byzantine faults in the first model, are significantly different from the round-based synchronous models. Another interesting side result of our study is that, contrary to the round-based synchronous consensus implementation for systems prone to mobile Byzantine faults, our storage emulation does not rely on the necessity of a core of correct processes all along the computation. That is, every server in the system can be compromised by the mobile Byzantine agents at some point in the computation. This leads to another interesting conclusion: storage is easier than consensus in synchronous settings, when the system is hit by mobile Byzantine failures

Integrated Development and Parallelization of Automated Dicentric Chromosome Identification Software to Expedite Biodosimetry Analysis

Manual cytogenetic biodosimetry lacks the ability to handle mass casualty events. We present an automated dicentric chromosome identification (ADCI) software utilizing parallel computing technology. A parallelization strategy combining data and task parallelism, as well as optimization of I/O operations, has been designed, implemented, and incorporated in ADCI. Experiments on an eight-core desktop show that our algorithm can expedite the process of ADCI by at least four folds. Experiments on Symmetric Computing, SHARCNET, Blue Gene/Q multi-processor computers demonstrate the capability of parallelized ADCI to process thousands of samples for cytogenetic biodosimetry in a few hours. This increase in speed underscores the effectiveness of parallelization in accelerating ADCI. Our software will be an important tool to handle the magnitude of mass casualty ionizing radiation events by expediting accurate detection of dicentric chromosomes

Consensus in Networks Prone to Link Failures

We consider deterministic distributed algorithms solving Consensus in synchronous networks of arbitrary topologies. Links are prone to failures. Agreement is understood as holding in each connected component of a network obtained by removing faulty links. We introduce the concept of stretch, which is a function of the number of connected components of a network and their respective diameters. Fast and early-stopping algorithms solving Consensus are defined by referring to stretch resulting in removing faulty links. We develop algorithms that rely only on nodes knowing their own names and the ability to associate communication with local ports. A network has $n$ nodes and it starts with $m$ functional links. We give a general algorithm operating in time $n$ that uses messages of $O(\log n)$ bits. If we additionally restrict executions to be subject to a bound $\Lambda$ on stretch, then there is a fast algorithm solving Consensus in time $O(\Lambda)$ using messages of $O(\log n)$ bits. Let $\lambda$ be an unknown stretch occurring in an execution; we give an algorithm working in time $(\lambda+2)^3$ and using messages of $O(n\log n)$ bits. We show that Consensus can be solved in the optimal $O(\lambda)$ time, but at the cost of increasing message size to $O(m\log n)$. We also demonstrate how to solve Consensus by an algorithm that uses only $O(n)$ non-faulty links and works in time $O(n m)$, while nodes start with their ports mapped to neighbors and messages carry $O(m\log n)$ bits. We prove lower bounds on performance of Consensus solutions that refer to parameters of evolving network topologies and the knowledge available to nodes

Wide-Area Time-Synchronized Closed-Loop Control of Power Systems And Decentralized Active Distribution Networks

The rapidly expanding power system grid infrastructure and the need to reduce the occurrence of major blackouts and prevention or hardening of systems against cyber-attacks, have led to increased interest in the improved resilience of the electrical grid. Distributed and decentralized control have been widely applied to computer science research. However, for power system applications, the real-time application of decentralized and distributed control algorithms introduce several challenges. In this dissertation, new algorithms and methods for decentralized control, protection and energy management of Wide Area Monitoring, Protection and Control (WAMPAC) and the Active Distribution Network (ADN) are developed to improve the resiliency of the power system. To evaluate the findings of this dissertation, a laboratory-scale integrated Wide WAMPAC and ADN control platform was designed and implemented. The developed platform consists of phasor measurement units (PMU), intelligent electronic devices (IED) and programmable logic controllers (PLC). On top of the designed hardware control platform, a multi-agent cyber-physical interoperability viii framework was developed for real-time verification of the developed decentralized and distributed algorithms using local wireless and Internet-based cloud communication. A novel real-time multiagent system interoperability testbed was developed to enable utility independent private microgrids standardized interoperability framework and define behavioral models for expandability and plug-and-play operation. The state-of-theart power system multiagent framework is improved by providing specific attributes and a deliberative behavior modeling capability. The proposed multi-agent framework is validated in a laboratory based testbed involving developed intelligent electronic device prototypes and actual microgrid setups. Experimental results are demonstrated for both decentralized and distributed control approaches. A new adaptive real-time protection and remedial action scheme (RAS) method using agent-based distributed communication was developed for autonomous hybrid AC/DC microgrids to increase resiliency and continuous operability after fault conditions. Unlike the conventional consecutive time delay-based overcurrent protection schemes, the developed technique defines a selectivity mechanism considering the RAS of the microgrid after fault instant based on feeder characteristics and the location of the IEDs. The experimental results showed a significant improvement in terms of resiliency of microgrids through protection using agent-based distributed communication