摘要:In this paper, we explore remarkable similarities between multi-transactional behaviors of smart contracts in cryptocurrencies such as Ethereum and classical problems of shared-memory concurrency. We examine two real-world examples from the Ethereum blockchain and an- alyzing how they are vulnerable to bugs that are closely reminiscent to those that often occur in traditional concurrent programs. We then elaborate on the relation between observable contract behaviors and well-studied concurrency topics, such as atomicity, interference, synchro- nization, and resource ownership. The described contracts-as-concurrent- objects analogy provides deeper understanding of potential threats for smart contracts, indicate better engineering practices, and enable appli- cations of existing state-of-the-art formal verification techniques.

摘要:ABSTRACT PBFT (Practical Byzantine Fault Tolerance) is one of the most popular consensus protocols of blockchain. However, in the PBFT, the enthusiasm of reliable nodes cannot be stimulated effectively, and a large amount of communication resources are used for data consistency. Therefore, a new consensus protocol — CDBFT (Credit-Delegated Byzantine Fault Tolerance) is proposed in this paper. CDBFT works as following: (1) a VRP(Voting Rewards and Punishments) scheme and its corresponding credit evaluation scheme are proposed not only to stimulate enthusiasm of reliable nodes but also to reduce the participation of abnormal nodes in the consensus process, and the virtuous circle of the system can be founded; (2) consistency and checkpoint protocols based on PBFT are proposed to improve the efficiency and flexibility of system. From the simulation results, a conclusion can be drawn, the participation probability of abnormal nodes in the consensus process can be reduced to 5%, and the efficiency and stability of the system are improved greatly in long-time running.

摘要:HoneyBadgerBFT, proposed by Miller et al. [35] as the first practical asyn- chronous atomic broadcast protocol, demonstrated impressive performance. The core of HoneyBadgerBFT (HB-BFT) is to achieve batching consensus using asynchronous common subset protocol (ACS) of Ben-Or et al., constituted with n reliable broadcast protocol (RBC) to have each node propose its input, followed by n asynchronous binary agreement protocol (ABA) to make a decision for each proposed value (n is the total number of nodes). In this paper, we propose two new atomic broadcast protocols (called Dumbo1, Dumbo2) both of which have asymptotically and practically better efficiency. In particular, the ACS of Dumbo1 only runs a small κ (independent of n) instances of ABA, while that of Dumbo2 further reduces it to constant! At the core of our techniques are two major observations: (1) reducing the number of ABA instances significantly improves efficiency; and (2) using multi-valued validated Byzantine agreement (MVBA) which was considered sub-optimal for ACS in [35] in a more careful way could actually lead to a much more efficient ACS. We implement both Dumbo1, Dumbo2 and deploy them as well as HB-BFT on 100 Amazon EC2 t2.medium instances uniformly distributed throughout 10 different regions across the globe, and run extensive experiments in the same environments. The experimental results show that our protocols achieve multi-fold improvements over HoneyBadgerBFT on both latency and throughput, especially when the system scale becomes moderately large.

摘要:Data,akeyassetinourdata-driveneconomy,hasfueled the emergence of a new data trading industry. However, there are a number of limitations in conventional data trading platforms due to the existence of dishonest buyer/data broker. To mitigate these limitations,weposittheimportanceofadataprocessing-as-a-service model,whichcomplementsconventionaldatahosting/exchange-as-aservice model. Specifically, in this paper, we introduce a secure data trading ecosystem and present a new blockchain-based data trading ecosystem (hereafter referred to as SDTE). In the ecosystem, both data broker and buyer are not able to obtain access to the seller’s raw data, as they are only getting access to the analysis findings that they require. In other words, we reduce the challenge of securing the dataset to the challenge to secure the data processing. We also build a security model to analyze the data trading market, and describe a new set of trading protocols for the entire data trading market. To demonstrate utility, we implement our proposed secure data trading platform (SDTP) on Ethereum & Intels Software Guard Extensions (SGX) and perform an in-depth analysis.

摘要:The surprising success of cryptocurrencies has led to a surge of interest in deploying large scale, highly robust, Byzantine fault tolerant (BFT) protocols for mission-critical applications, such as financial transactions. Although the conventional wisdom is to build atop a (weakly) synchronous protocol such as PBFT (or a variation thereof), such protocols rely critically on network timing assumptions, and only guarantee liveness when the network behaves as expected. We argue these protocols are ill-suited for this deployment scenario. We present an alternative, HoneyBadgerBFT, the first practical asynchronous BFT protocol, which guarantees liveness without making any timing assumptions. We base our solution on a novel atomic broadcast protocol that achieves optimal asymptotic efficiency. We present an implementation and experimental results to show our system can achieve throughput of tens of thousands of transactions per second, and scales to over a hundred nodes on a wide area network. We even conduct BFT experiments over Tor, without needing to tune any parameters. Unlike the alternatives, HoneyBadgerBFT simply does not care about the underlying network.

摘要:Reliablecomputersystems musthandlemalfunctioningcomponentsthat giveconflictinginformation to different parts of the system. This situation can be expressed abstractly in terms of a group of generals of the Byzantine army camped with their troops around an enemy city. Communicatingonly by messenger, the generals must agree upon a common battle plan. However, one or more of them may be traitors who will try to confuse the others. The problem is to find an algorithm to ensure that the loyal generals will reach agreement. It is shown that, using only oral messages, this problem is solvable if and only if more than two-thirds of the generals are loyal; so a single traitor can confound two loyal generals. With unforgeable written messages, the problem is solvable for any number of generals and possible traitors. Applications of the solutions to reliable computer systems are then discussed.