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Register a new userOstraka: Secure Blockchain Scaling by Node Sharding
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Added by
Alex Manuskin
Publication date
2019
fields
Informatics Engineering
and research's language is
English
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Cryptocurrencies, implemented with blockchain protocols, promise to become a global payment system if they can overcome performance limitations. Rapidly advancing architectures improve on latency and throughput, but most require all participating servers to process all transactions. Several recent works propose to shard the system, such that each machine would only process a subset of the transactions. However, we identify a denial-of-service attack that is exposed by these solutions - an attacker can generate transactions that would overload a single shard, thus delaying processing in the entire system. Moreover, we show that in common scenarios, these protocols require most node operators to process almost all blockchain transactions. We present Ostraka, a blockchain node architecture that shards (parallelizes) the nodes themselves. We prove that replacing a unified node with an Ostraka node does not affect the security of the underlying consensus mechanism. We evaluate analytically and experimentally block propagation and processing in various settings. Ostraka allows nodes in the network to scale, without costly coordination. In our experiments, Ostraka nodes transaction processing rate grows linearly with the addition of resources.
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Existing blockchain systems scale poorly because of their distributed consensus protocols. Current attempts at improving blockchain scalability are limited to cryptocurrency. Scaling blockchain systems under general workloads (i.e., non-cryptocurrency applications) remains an open question. In this work, we take a principled approach to apply sharding, which is a well-studied and proven technique to scale out databases, to blockchain systems in order to improve their transaction throughput at scale. This is challenging, however, due to the fundamental difference in failure models between databases and blockchain. To achieve our goal, we first enhance the performance of Byzantine consensus protocols, by doing so we improve individual shards throughput. Next, we design an efficient shard formation protocol that leverages a trusted random beacon to securely assign nodes into shards. We rely on trusted hardware, namely Intel SGX, to achieve high performance for both consensus and shard formation protocol. Third, we design a general distributed transaction protocol that ensures safety and liveness even when transaction coordinators are malicious. Finally, we conduct an extensive evaluation of our design both on a local cluster and on Google Cloud Platform. The results show that our consensus and shard formation protocols outperform state-of-the-art solutions at scale. More importantly, our sharded blockchain reaches a high throughput that can handle Visa-level workloads, and is the largest ever reported in a realistic environment.
Federated learning (FL) has emerged as a promising master/slave learning paradigm to alleviate systemic privacy risks and communication costs incurred by cloud-centric machine learning methods. However, it is very challenging to resist the single point of failure of the master aggregator and attacks from malicious participants while guaranteeing model convergence speed and accuracy. Recently, blockchain has been brought into FL systems transforming the paradigm to a decentralized manner thus further improve the system security and learning reliability. Unfortunately, the traditional consensus mechanism and architecture of blockchain systems can hardly handle the large-scale FL task due to the huge resource consumption, limited transaction throughput, and high communication complexity. To address these issues, this paper proposes a two-layer blockchaindriven FL framework, called as ChainsFL, which is composed of multiple subchain networks (subchain layer) and a direct acyclic graph (DAG)-based mainchain (mainchain layer). In ChainsFL, the subchain layer limits the scale of each shard for a small range of information exchange, and the mainchain layer allows each shard to share and validate the learning model in parallel and asynchronously to improve the efficiency of cross-shard validation. Furthermore, the FL procedure is customized to deeply integrate with blockchain technology, and the modified DAG consensus mechanism is proposed to mitigate the distortion caused by abnormal models. In order to provide a proof-ofconcept implementation and evaluation, multiple subchains base on Hyperledger Fabric are deployed as the subchain layer, and the self-developed DAG-based mainchain is deployed as the mainchain layer. The experimental results show that ChainsFL provides acceptable and sometimes better training efficiency and stronger robustness compared with the typical existing FL systems.
Many blockchain consensus protocols have been proposed recently to scale the throughput of a blockchain with available bandwidth. However, these protocols are becoming increasingly complex, making it more and more difficult to produce proofs of their security guarantees. We propose a novel permissionless blockchain protocol OHIE which explicitly aims for simplicity. OHIE composes as many parallel instances of Bitcoins original (and simple) backbone protocol as needed to achieve excellent throughput. We formally prove the safety and liveness properties of OHIE. We demonstrate its performance with a prototype implementation and large-scale experiments with up to 50,000 nodes. In our experiments, OHIE achieves linear scaling with available bandwidth, providing about 4-10 Mbps transaction throughput (under 8-20 Mbps per-node available bandwidth configurations) and at least about 20x better decentralization over prior works.
Blockchain is an incrementally updated ledger maintained by distributed nodes rather than centralized organizations. The current blockchain technology faces scalability issues, which include two aspects: low transaction throughput and high storage capacity costs. This paper studies the blockchain structure based on state sharding technology, and mainly solves the problem of non-scalability of block chain storage. This paper designs and implements the blockchain state sharding scheme, proposes a specific state sharding data structure and algorithm implementation, and realizes a complete blockchain structure so that the blockchain has the advantages of high throughput, processing a large number of transactions and saving storage costs. Experimental results show that a blockchain network with more than 100,000 nodes can be divided into 1024 shards. A blockchain network with this structure can process 500,000 transactions in about 5 seconds. If the consensus time of the blockchain is about 10 seconds, and the block generation time of the blockchain system of the sharding mechanism is 15 seconds, the transaction throughput can reach 33,000 tx/sec. Experimental results show that the throughput of the proposed protocol increases with the increase of the network node size. This confirms the scalability of the blockchain structure based on sharding technology.
To promote the benefits of the Internet of Things (IoT) in smart communities and smart cities, a real-time data marketplace middleware platform, called the Intelligent IoT Integrator (I3), has been recently proposed. While facilitating the easy exchanges of real-time IoT data streams between device owners and third-party applications through the marketplace, I3 is presently a monolithic, centralized platform for a single community. Although the service oriented architecture (SOA) has been widely adopted in the IoT and cyber-physical systems (CPS), it is difficult for a monolithic architecture to provide scalable, inter-operable and extensible services for large numbers of distributed IoT devices and different application vendors. Traditional security solutions rely on a centralized authority, which can be a performance bottleneck or susceptible to a single point of failure. Inspired by containerized microservices and blockchain technology, this paper proposed a BLockchain-ENabled Secure Microservices for Decentralized Data Marketplaces (BlendSM-DDM). Within a permissioned blockchain network, a microservices based security mechanism is introduced to secure data exchange and payment among participants in the marketplace. BlendSM-DDM is able to offer a decentralized, scalable and auditable data exchanges for the data marketplace.
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