Most popular blockchain solutions, like Bitcoin, rely on proof-of-work, guaranteeing that the output of the consensus is agreed upon with high probability. However, this probability depends on the delivery of messages and that the computational power of the system is sufficiently scattered among pools of nodes in the network so that no pool can mine more blocks faster than the crowd. New approaches, like Ethereum, generalise the proof-of-work approach by letting individuals deploy their own private blockchain with high transaction throughput. As companies are starting to deploy private chains, it has become crucial to better understand the guarantees blockchains offer in such a small and controlled environment. In this paper, we present the , an execution that we experienced when building our private chain at NICTA Data61. Even though this anomaly has never been acknowledged before, it may translate into dramatic consequences for the user of blockchains. Named after the infamous Paxos anomaly, this anomaly makes dependent transactions, like "Bob sends money to Carole after he received money from Alice" impossible. This anomaly relies on the fact that existing blockchains do not ensure consensus safety deterministically: there is no way for Bob to make sure that Alice actually sent him coins without Bob using an external mechanism, like converting these coins into a fiat currency that allows him to withdraw. We also explore smart contracts as a potential alternative to transactions in order to freeze coins, and show implementations of smart contract that can suffer from the Blockchain anomaly and others that may cope with it.
Tendermint http: tendermint.com . is a blockchain system building upon proof-of-stake. It is known to favour consistency over availability, taking the opposite view of Casper, the proof-of-stake alternative to the Ghost protocol. The Tendermint consensus protocol builds upon the Byzantine agreement protocol with authentication @cite_1 and requires strictly more than two third of correct processes to ensure agreement and validity deterministically and to guarantee termination when the network stabilises and messages between non-faulty nodes get delivered.
@cite_1
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We introduce Casper, a proof of stake-based finality system which overlays an existing proof of work blockchain. Casper is a partial consensus mechanism combining proof of stake algorithm research and Byzantine fault tolerant consensus theory. We introduce our system, prove some desirable features, and show defenses against long range revisions and catastrophic crashes. The Casper overlay provides almost any proof of work chain with additional protections against block reversions. This paper introduces a new leaderless Byzantine consensus called the Democratic Byzantine Fault Tolerance (DBFT) for blockchains. While most blockchain consensus protocols rely on a correct leader or coordinator to terminate, our algorithm can terminate even when its coordinator is faulty. The key idea is to allow processes to complete asynchronous rounds as soon as they receive a threshold of messages, instead of having to wait for a message from a coordinator that may be slow. The resulting decentralization is particularly appealing for blockchains for two reasons: (i) each node plays a similar role in the execution of the consensus, hence making the decision inherently “democratic” (ii) decentralization avoids bottlenecks by balancing the load, making the solution scalable. DBFT is deterministic, assumes partial synchrony, is resilience optimal, time optimal and does not need signatures. We first present a simple safe binary Byzantine consensus algorithm, modify it to ensure termination, and finally present an optimized reduction from multivalue consensus to binary consensus whose fast path terminates in 4 message delays. The surging interest in blockchain technology has revitalized the search for effective Byzantine consensus schemes. In particular, the blockchain community has been looking for ways to effectively integrate traditional Byzantine fault-tolerant (BFT) protocols into a blockchain consensus layer allowing various financial institutions to securely agree on the order of transactions. However, existing BFT protocols can only scale to tens of nodes due to their @math message complexity. In this paper, we propose FastBFT, a fast and scalable BFT protocol. At the heart of FastBFT is a novel message aggregation technique that combines hardware-based trusted execution environments (TEEs) with lightweight secret sharing. Combining this technique with several other optimizations (i.e., optimistic execution, tree topology and failure detection), FastBFT achieves low latency and high throughput even for large scale networks. Via systematic analysis and experiments, we demonstrate that FastBFT has better scalability and performance than previous BFT protocols. Abstract A consensus protocol enables a system of n asynchronous processes, some of them faulty, to reach agreement. Both the processes and the message system are capable of cooperating to prevent the correct processes from reaching decision. A protocol is t -resilient if in the presence of up to t faulty processes it reaches agreement with probability 1. Byzantine processes are faulty processes that can deviate arbitrarily from the protocol; Fail-Stop processes can just stop participating in it. In a recent paper, t -resilient randomized consensus protocols were presented for t n 5 . We improve this to t n 3 , thus matching the known lower bound on the number of correct processes necessary for consensus. The protocol uses a general technique in which the behavior of the Byzantine processes is restricted by the use of a broadcast protocol that filters some of the messages. The apparent behavior of the Byzantine processes, filtered by the broadcast protocol, is similar to that of Fail-Stop processes. Plugging the broadcast protocol as a communicating primitive into an agreement protocol for Fail-Stop processes gives the result. This technique, of using broadcast protocols to reduce the power of the faulty processes and then using them as communication primitives in algorithms designed for weaker failure models, was used succesfully in other contexts.