728 research outputs found
ARPA Whitepaper
We propose a secure computation solution for blockchain networks. The
correctness of computation is verifiable even under malicious majority
condition using information-theoretic Message Authentication Code (MAC), and
the privacy is preserved using Secret-Sharing. With state-of-the-art multiparty
computation protocol and a layer2 solution, our privacy-preserving computation
guarantees data security on blockchain, cryptographically, while reducing the
heavy-lifting computation job to a few nodes. This breakthrough has several
implications on the future of decentralized networks. First, secure computation
can be used to support Private Smart Contracts, where consensus is reached
without exposing the information in the public contract. Second, it enables
data to be shared and used in trustless network, without disclosing the raw
data during data-at-use, where data ownership and data usage is safely
separated. Last but not least, computation and verification processes are
separated, which can be perceived as computational sharding, this effectively
makes the transaction processing speed linear to the number of participating
nodes. Our objective is to deploy our secure computation network as an layer2
solution to any blockchain system. Smart Contracts\cite{smartcontract} will be
used as bridge to link the blockchain and computation networks. Additionally,
they will be used as verifier to ensure that outsourced computation is
completed correctly. In order to achieve this, we first develop a general MPC
network with advanced features, such as: 1) Secure Computation, 2) Off-chain
Computation, 3) Verifiable Computation, and 4)Support dApps' needs like
privacy-preserving data exchange
A Consensus Algorithm Based on Risk Assessment Model for Permissioned Blockchain
Blockchain technology enables stakeholders to conduct trusted data sharing
and exchange without a trusted centralized institution. These features make
blockchain applications attractive to enhance trustworthiness in very different
contexts. Due to unique design concepts and outstanding performance, blockchain
has become a popular research topic in industry and academia in recent years.
Every participant is anonymous in a permissionless blockchain represented by
cryptocurrency applications such as Bitcoin. In this situation, some special
incentive mechanisms are applied to permissionless blockchain, such as mined
native cryptocurrency to solve the trust issues of permissionless blockchain.
In many use cases, permissionless blockchain has bottlenecks in transaction
throughput performance, which restricts further application in the real world.
A permissioned blockchain can reach a consensus among a group of entities that
do not establish an entire trust relationship. Unlike permissionless
blockchains, the participants must be identified in permissioned blockchains.
By relying on the traditional crash fault-tolerant consensus protocols,
permissioned blockchains can achieve high transaction throughput and low
latency without sacrificing security. However, how to balance the security and
consensus efficiency is still the issue that needs to be solved urgently in
permissioned blockchains. As the core module of blockchain technology, the
consensus algorithm plays a vital role in the performance of the blockchain
system. Thus, this paper proposes a new consensus algorithm for permissioned
blockchain, the Risk Assessment-based Consensus protocol (RAC), combined with
the decentralized design concept and the risk-node assessment mechanism to
address the unbalance issues of performance in speed, scalability, and
security.Comment: 32 pages, 11 figure
Study of consensus protocols and improvement of the Federated Byzantine Agreement (FBA) algorithm
At a present time, it has been proven that blockchain technology has influenced to a great extent the way of human interaction in a digital world. The operation of the blockchain systems allows the peers to implement digital transactions in a Peer to Peer (P2P) network in a direct way without the need of third parties. Each blockchain determines different rules for the record of the transactions in the ledger. The transactions are inserted in blocks and each one, in turn, is appended to the chain (ledger) based on different consensus algorithms. Once blocks have been inserted in the chain, the consensus has been reached and the blocks with corresponding transactions are considered immutable. This thesis analyses the main features of the blockchain and how the consensus can be achieved through the different kinds of consensus algorithms. In addition, a detailed reference for Stellar and Federated Byzantine Agreement (FBA) consensus protocols is made in order to explain these algorithms, their limitations as well as their improvement. The development of a reputation mechanism is necessary to the improvement of above algorithms
On Cyber Risk Management of Blockchain Networks: A Game Theoretic Approach
Open-access blockchains based on proof-of-work protocols have gained
tremendous popularity for their capabilities of providing decentralized
tamper-proof ledgers and platforms for data-driven autonomous organization.
Nevertheless, the proof-of-work based consensus protocols are vulnerable to
cyber-attacks such as double-spending. In this paper, we propose a novel
approach of cyber risk management for blockchain-based service. In particular,
we adopt the cyber-insurance as an economic tool for neutralizing cyber risks
due to attacks in blockchain networks. We consider a blockchain service market,
which is composed of the infrastructure provider, the blockchain provider, the
cyber-insurer, and the users. The blockchain provider purchases from the
infrastructure provider, e.g., a cloud, the computing resources to maintain the
blockchain consensus, and then offers blockchain services to the users. The
blockchain provider strategizes its investment in the infrastructure and the
service price charged to the users, in order to improve the security of the
blockchain and thus optimize its profit. Meanwhile, the blockchain provider
also purchases a cyber-insurance from the cyber-insurer to protect itself from
the potential damage due to the attacks. In return, the cyber-insurer adjusts
the insurance premium according to the perceived risk level of the blockchain
service. Based on the assumption of rationality for the market entities, we
model the interaction among the blockchain provider, the users, and the
cyber-insurer as a two-level Stackelberg game. Namely, the blockchain provider
and the cyber-insurer lead to set their pricing/investment strategies, and then
the users follow to determine their demand of the blockchain service.
Specifically, we consider the scenario of double-spending attacks and provide a
series of analytical results about the Stackelberg equilibrium in the market
game
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