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aviors [22]–[26]. In addition, Sharples and Domingue proposed a blockchain-based permanent distributed record of intellectual effort which instantiates and democra- tises educational reputation beyond the academic communi- ty [27]. In [28], authors proposed a new blockchain-based fair payment to study the cyber physical system (CPS), in which reputation system is applied such that a subscriber evaluate the published event and mark the publisher based on the reputation. In this paper, we propose a new rep
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Incentivizing Honest Mining in Blockchain Networks A Reputation Approach
100
utation-based mecha- nism to incentivize miners to conduct honest mining, thereby promote the efficient of bitcoin system. Specifically, we first describe the system model in term of PoW-based blockchain network, where miners present some malicious behaviors during the mining process. We then design a reputation mech- 1549-7747 (c) 2018 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.htm
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Incentivizing Honest Mining in Blockchain Networks A Reputation Approach
101
l for more information. This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TCSII.2019.2901746, IEEE Transactions on Circuits and Systems II: Express Briefs 2 anism based on the interval estimation and the fluctuation of reputation to incentive the honest mining for miners, in which the reputation depends on the historical evaluation. We find that the pool manage
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Incentivizing Honest Mining in Blockchain Networks A Reputation Approach
102
r strictly selects high-quality miners based on the reputation mechanism we proposed, which contributes understanding for PoW consensus algorithm and provides a new method to explore the bitcoin system. II. SYSTEM MODEL AND REPUTATION MECHANISM A. System Model Consider a PoW-based blockchain network with J individ- ual miners, which organize themselves into I mining pools in solving a crypto-puzzle competition to win the reward. According to the Nakamoto Consensus protocol [1], only the pool which acco
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Incentivizing Honest Mining in Blockchain Networks A Reputation Approach
103
mplishes the PoW firstly will be rewarded. Therefore, we pay our attention to the payoff of miners in the target pool. Define the strategy set of miners as S =
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Incentivizing Honest Mining in Blockchain Networks A Reputation Approach
104
State of the Art and Challenges Facing Consensus Protocols on Blockchain Nutthakorn Chalaemwongwan Information Science and Technology Mahanakorn University of Technology Bangkok, Thailand [email protected] Werasak Kurutach Information Science and Technology Mahanakorn University of Technology Bangkok, Thailand [email protected] Abstractβ€”Nowadays, the blockchain is a favorite platform, for instance, for use with cryptocurrency, smart contracts, IoT, and
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State of the art and challenges facing consensus p
105
State of the Art and Challenges Facing Consensus Protocols on Blockchain Nutthakorn Chalaemwongwan Information Science and Technology Mahanakorn University of Technology Bangkok, Thailand [email protected] Werasak Kurutach Information Science and Technology Mahanakorn University of Technology Bangkok, Thailand [email protected] Abstractβ€”Nowadays, the blockchain is a favorite platform, for instance, for use with cryptocurrency, smart contracts, IoT, and
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State of the art and challenges facing consensus p
106
so forth. Blockchains are distributed ledgers that enable parties who do not trust each other to maintain states. The parties agree on the existence, values, and histories of the states. The blockchain applies the consensus protocol to verify the block which is distributing the network node. Consensus has many practices such as, for example, Byzantine general problem, Proof of work, and Proof of stake. However, there have not been numerous papers that have undertaken analysis with regard to
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State of the art and challenges facing consensus p
107
so forth. Blockchains are distributed ledgers that enable parties who do not trust each other to maintain states. The parties agree on the existence, values, and histories of the states. The blockchain applies the consensus protocol to verify the block which is distributing the network node. Consensus has many practices such as, for example, Byzantine general problem, Proof of work, and Proof of stake. However, there have not been numerous papers that have undertaken analysis with regard to
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State of the art and challenges facing consensus p
108
various aspects, and which have incorporated the adoption summary as appropriate to the application. In this paper, we have provided a technical verification review with regard to the consensus algorithm taken from previous research. The audience will receive a consensus protocol, and the algorithm typically analyzes the application to match which platform is appropriate by viewing the node identity, energy saving and the tolerated power of the adversary, the data model, language, executio
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State of the art and challenges facing consensus p
109
various aspects, and which have incorporated the adoption summary as appropriate to the application. In this paper, we have provided a technical verification review with regard to the consensus algorithm taken from previous research. The audience will receive a consensus protocol, and the algorithm typically analyzes the application to match which platform is appropriate by viewing the node identity, energy saving and the tolerated power of the adversary, the data model, language, executio
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State of the art and challenges facing consensus p
110
n, application, and examples. Finally, we finish by presenting several research directions with regard to the consensus protocol. Keywords: blockchain; consensus; distributed ledger; distributed consensus; consensus algorithms I. INTRODUCTION A ledger is a documentary framework which includes an ordered record of transactions. For instance, a ledger will record transactions between several commercial banks, or goods exchanged with known parties. An aspect of blockchains is that the le
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State of the art and challenges facing consensus p
111
n, application, and examples. Finally, we finish by presenting several research directions with regard to the consensus protocol. Keywords: blockchain; consensus; distributed ledger; distributed consensus; consensus algorithms I. INTRODUCTION A ledger is a documentary framework which includes an ordered record of transactions. For instance, a ledger will record transactions between several commercial banks, or goods exchanged with known parties. An aspect of blockchains is that the le
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State of the art and challenges facing consensus p
112
dger is replicated entirely on almost all the nodes. Moreover, transactions are assembled into blocks, then chained to one another. Therefore, the distributed ledger is a replicated attach only data framework. A blockchain begins with the initial states, while the ledger records all the history of the revision procedure. A technique encouraging distributed ledgers could classify them in terms of three aspects. (Account, Asset, and Coin). Initially, the application created on the top of the
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State of the art and challenges facing consensus p
113
dger is replicated entirely on almost all the nodes. Moreover, transactions are assembled into blocks, then chained to one another. Therefore, the distributed ledger is a replicated attach only data framework. A blockchain begins with the initial states, while the ledger records all the history of the revision procedure. A technique encouraging distributed ledgers could classify them in terms of three aspects. (Account, Asset, and Coin). Initially, the application created on the top of the
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State of the art and challenges facing consensus p
114
ledger establishes the information entirely in such a way as to keep within the ledger A cryptocurrency application will use to create a user account similar to that found in conventional banking. The intention is that it is simple to build and apply a lower level model such as an example table or a critical value as mentioned. Second, the functional system might have one or higher ledgers which can link to one another. A large enterprise, for instance, may have multiple ledgers, one for
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State of the art and challenges facing consensus p
115
ledger establishes the information entirely in such a way as to keep within the ledger A cryptocurrency application will use to create a user account similar to that found in conventional banking. The intention is that it is simple to build and apply a lower level model such as an example table or a critical value as mentioned. Second, the functional system might have one or higher ledgers which can link to one another. A large enterprise, for instance, may have multiple ledgers, one for
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State of the art and challenges facing consensus p
116
every department such as engineering, sales, supply chain, payroll, and so forth. Finally, ledger possession can fluctuate significantly from being exposed entirely to the public to being totally managed by one participant. Bitcoin, for instance, was presented and, as a result, makes people think that it is costly to determine who will update the public ledger. Parity [1] predefines some owners who adjust the public ledger simply by adding their signature to the blocks. The information c
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State of the art and challenges facing consensus p
117
every department such as engineering, sales, supply chain, payroll, and so forth. Finally, ledger possession can fluctuate significantly from being exposed entirely to the public to being totally managed by one participant. Bitcoin, for instance, was presented and, as a result, makes people think that it is costly to determine who will update the public ledger. Parity [1] predefines some owners who adjust the public ledger simply by adding their signature to the blocks. The information c
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State of the art and challenges facing consensus p
118
ontained in the ledger demonstrates the history of transactions up to the current time through the blockchain. Updates to the ledger should be consented to by every participant. Specifically, several participants need to agree with a consensus. Observing which it is may not be the situation found in countless real-world applications such as a fiat digital currency, by which a single entity (e.g., a bank or a government) decides on the updates. The importance of a blockchain strategy is
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State of the art and challenges facing consensus p
119
actually being able to deal with those nodes that do not trust working together, indicating which variables might respond in Byzantine formality. The consensus protocol consequently needs to endure Byzantine problems. The research involving a survey on consensus was comprehensive, and there are numerous versions of previously recommended protocols that have been manufactured for blockchains [2]. These could be categorized in terms of their combined range. Overwhelming consists of solely
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State of the art and challenges facing consensus p
120
actually being able to deal with those nodes that do not trust working together, indicating which variables might respond in Byzantine formality. The consensus protocol consequently needs to endure Byzantine problems. The research involving a survey on consensus was comprehensive, and there are numerous versions of previously recommended protocols that have been manufactured for blockchains [2]. These could be categorized in terms of their combined range. Overwhelming consists of solely
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State of the art and challenges facing consensus p
121
computation-based protocols in which the users utilize proof of computation to find a node that arbitrarily determines the next operation. Bitcoin's Proof of work (PoW) is a simple example of the consensus. The other severe are solely communication-based protocols for which nodes have matching votes and run through several rounds of communication to achieve consensus. All protocols, Practical Byzantine Fault Tolerance (PBFT) [3] being the best illustration, are applied in particular config
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State of the art and challenges facing consensus p
122
computation-based protocols in which the users utilize proof of computation to find a node that arbitrarily determines the next operation. Bitcoin's Proof of work (PoW) is a simple example of the consensus. The other severe are solely communication-based protocols for which nodes have matching votes and run through several rounds of communication to achieve consensus. All protocols, Practical Byzantine Fault Tolerance (PBFT) [3] being the best illustration, are applied in particular config
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State of the art and challenges facing consensus p
123
urations because they take authenticated nodes. In the middle, all opposites we find mixed consensus protocols that intend to increase the efficiency of PBFT and PoW. As an example, Proof of Elapsed Time removes the need for costly mining at PoW with the use of profiting reliable devices. The other illustration is 957978-1-5386-2290-2/18/$31.00 Β©2018 IEEE ICOIN 2018 Proof of Authority [4] which helps PBFT by pre-finding trusted nodes in which users vote on their own in order to achieve
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State of the art and challenges facing consensus p
124
consensus. Likewise, Stellar [5] and Ripple [6] augment PBFT by achieving consensus in smaller networks. In the next section, we provide related work associated with consensus protocol. Part III explains consensus protocol comparisons which are used in Section IV for analysis purposes. Section V offers a conclusion with regard to the survey of consensus protocols, and section VI deals with future research directions. II. RELATED WORK A. CAP Theorem CAP Theorem [7] is a system that di
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State of the art and challenges facing consensus p
125
consensus. Likewise, Stellar [5] and Ripple [6] augment PBFT by achieving consensus in smaller networks. In the next section, we provide related work associated with consensus protocol. Part III explains consensus protocol comparisons which are used in Section IV for analysis purposes. Section V offers a conclusion with regard to the survey of consensus protocols, and section VI deals with future research directions. II. RELATED WORK A. CAP Theorem CAP Theorem [7] is a system that di
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State of the art and challenges facing consensus p
126
stributes multiple nodes that handle common data, and shows which distributed systems can completely satisfy the following three properties: Consistency (C) is a status by which each node has the latest data at the same time. Availability (A) is the status where any failure of a specific node does not affect other nodes. Partition tolerance (P) is the status by which nodes can continue operations, even with a failure in the network. The blockchain is one of the distributed systems which can sa
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State of the art and challenges facing consensus p
127
tisfy both availability (A) and partition tolerance (P) but cannot satisfy the condition of consistency (C). Instead, as long as the separation of the network is time-limited, the system is regarded as maintaining the ultimate consistency. Ultimate consistency is
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State of the art and challenges facing consensus p
128
tisfy both availability (A) and partition tolerance (P) but cannot satisfy the condition of consistency (C). Instead, as long as the separation of the network is time-limited, the system is regarded as maintaining the ultimate consistency. Ultimate consistency is
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State of the art and challenges facing consensus p
129
Attack Incentive and Security of Exchanging Tokens on Proof-of-Work Blockchain AUTHORS ABSTRACT In a consensus algorithm based on Proof-of-Work, miners are motivated by crypto rewards. Furthermore, security is guaranteed because a cost of a 50% attack chance is higher than the potential rewards. However, because of the sudden price jump of cryptocurrencies and cheap prices of mining machines like ASICs, the cost and profit were on equilibrium for Bitcoin in 2017. In this situation, attackers are motiv
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Attack Incentive and Security of Exchanging Tokens on Proof of Work Blockchain
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ated by the balance between hash power and profits. In this paper, we describe that there is relevance between mining power on the network and price oftokens that can be taken securely on a blockchain. Users who exchange tokens on the PoW blockchain should monitor mining power and exchange tokens cheaper than the attack cost so that profit and cost of the attacker are not in equilibrium. CCS CONCEPTS Security and privacy, Distributed systems security, Computing methodologies, Modeling and simulation KE
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Attack Incentive and Security of Exchanging Tokens on Proof of Work Blockchain
131
ated by the balance between hash power and profits. In this paper, we describe that there is relevance between mining power on the network and price oftokens that can be taken securely on a blockchain. Users who exchange tokens on the PoW blockchain should monitor mining power and exchange tokens cheaper than the attack cost so that profit and cost of the attacker are not in equilibrium. CCS CONCEPTS Security and privacy, Distributed systems security, Computing methodologies, Modeling and simulation KE
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Attack Incentive and Security of Exchanging Tokens on Proof of Work Blockchain
132
YWORDS Blockchain, Proof-of-Work, Token exchange ACM SECTION: INTRODUCTION Bitcoin is a peer-to-peer electronic payment system [20]. Each node record transaction data (TXs) on a ledger stored in them and verify TXs are not conflicting by referencing the ledger. The ledger is called β€œBlockchain” and nodes make consensus so that the ledger each node holds keeps consistency. To make a consensus, Bitcoin uses Proof-of-Work (PoW) in the form of a mathematical puzzle that a user can solve by spending comput
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Attack Incentive and Security of Exchanging Tokens on Proof of Work Blockchain
133
YWORDS Blockchain, Proof-of-Work, Token exchange ACM SECTION: INTRODUCTION Bitcoin is a peer-to-peer electronic payment system [20]. Each node record transaction data (TXs) on a ledger stored in them and verify TXs are not conflicting by referencing the ledger. The ledger is called β€œBlockchain” and nodes make consensus so that the ledger each node holds keeps consistency. To make a consensus, Bitcoin uses Proof-of-Work (PoW) in the form of a mathematical puzzle that a user can solve by spending comput
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Attack Incentive and Security of Exchanging Tokens on Proof of Work Blockchain
134
ational power. Because a node that finds the answer can get cryptocurrencies as rewards, using the metaphor of gold mining, the process of solving PoW is called β€œmining.” The consensus mechanism based on PoWis secure unless an attacker obtains over 50% ofcomputational power in the network. Additionally, security guaranteed by the cost of 50% attack is not in equilibrium with profits. However, by the sudden price jump of cryptocurrencies and cheaply of mining machines like ASICs, the cost was in equilibri
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Attack Incentive and Security of Exchanging Tokens on Proof of Work Blockchain
135
ational power. Because a node that finds the answer can get cryptocurrencies as rewards, using the metaphor of gold mining, the process of solving PoW is called β€œmining.” The consensus mechanism based on PoWis secure unless an attacker obtains over 50% ofcomputational power in the network. Additionally, security guaranteed by the cost of 50% attack is not in equilibrium with profits. However, by the sudden price jump of cryptocurrencies and cheaply of mining machines like ASICs, the cost was in equilibri
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Attack Incentive and Security of Exchanging Tokens on Proof of Work Blockchain
136
um for Bitcoin in 2017. In this situation, the mining cost is not a disincentive for attackers because that they can get rewards proportional to the cost of the attack. In a 50% attack, the attacker can get cryptocurrency as the reward and profit of attack and can estimate the cost from the network’s hash power. In Bitcoin, if a 50% attack is detected, the price ofBitcoins will fall so it serves as a disincentive for attackers. In Ethereum [27], the price of tokens (e.g., lands described by ERC-20 [12])
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Attack Incentive and Security of Exchanging Tokens on Proof of Work Blockchain
137
um for Bitcoin in 2017. In this situation, the mining cost is not a disincentive for attackers because that they can get rewards proportional to the cost of the attack. In a 50% attack, the attacker can get cryptocurrency as the reward and profit of attack and can estimate the cost from the network’s hash power. In Bitcoin, if a 50% attack is detected, the price ofBitcoins will fall so it serves as a disincentive for attackers. In Ethereum [27], the price of tokens (e.g., lands described by ERC-20 [12])
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Attack Incentive and Security of Exchanging Tokens on Proof of Work Blockchain
138
is sometimes not affected by network security. Therefore, attackers are motivated by the balance between hash power and profits. We described that there is relevant between mining power on the network and price of tokens that a user can take on a blockchain. Users who exchange tokens on the PoW blockchain should monitor mining power and exchange tokens cheaper than attack cost so that profits and costs of the attacker is not equilibrium. SECTION: BLOCKCHAIN Blockchain is a system in which each node kee
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Attack Incentive and Security of Exchanging Tokens on Proof of Work Blockchain
139
is sometimes not affected by network security. Therefore, attackers are motivated by the balance between hash power and profits. We described that there is relevant between mining power on the network and price of tokens that a user can take on a blockchain. Users who exchange tokens on the PoW blockchain should monitor mining power and exchange tokens cheaper than attack cost so that profits and costs of the attacker is not equilibrium. SECTION: BLOCKCHAIN Blockchain is a system in which each node kee
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Attack Incentive and Security of Exchanging Tokens on Proof of Work Blockchain
140
ps an append-only ledger, and by the appending rule the ledger keeps consistency even though each node operates independently. FOOTNOTE: In this paper, Blockchain means the system, a blockchain means the ledger that each node keeps. In Bitcoin, each node can verify transactions of cryptocurrencies by referring to a blockchain that is stored locally. Hence, nodes can detect β€œdouble-spending” in which an attacker pays the same cryptocurrency to different users. Each node stores a set of verified transact
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Attack Incentive and Security of Exchanging Tokens on Proof of Work Blockchain
141
ps an append-only ledger, and by the appending rule the ledger keeps consistency even though each node operates independently. FOOTNOTE: In this paper, Blockchain means the system, a blockchain means the ledger that each node keeps. In Bitcoin, each node can verify transactions of cryptocurrencies by referring to a blockchain that is stored locally. Hence, nodes can detect β€œdouble-spending” in which an attacker pays the same cryptocurrency to different users. Each node stores a set of verified transact
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Attack Incentive and Security of Exchanging Tokens on Proof of Work Blockchain
142
ions as β€œBlock” in a blockchain. A block includes the cryptographic hash number of the last one in the blockchain. By this structure, if an attacker rewrites a previous transaction, the hash number of a block that includes it is changed, and the hash of the next one is changed too. Hence, an attacker needs to update all blocks starting from the rewritten one to the last one. To keep consistency and difficulty of rewriting, block maker needs to solve a mathematical puzzle called β€œProof-of-Work(PoW)” and i
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Attack Incentive and Security of Exchanging Tokens on Proof of Work Blockchain
143
ions as β€œBlock” in a blockchain. A block includes the cryptographic hash number of the last one in the blockchain. By this structure, if an attacker rewrites a previous transaction, the hash number of a block that includes it is changed, and the hash of the next one is changed too. Hence, an attacker needs to update all blocks starting from the rewritten one to the last one. To keep consistency and difficulty of rewriting, block maker needs to solve a mathematical puzzle called β€œProof-of-Work(PoW)” and i
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Attack Incentive and Security of Exchanging Tokens on Proof of Work Blockchain
144
nclude the answer in the new block. PoW has the characteristics that solving needs much computational power but verifying the answer is simple. If some block maker makes blocks that include conflicting transactions by rewriting the past, nodes detect the conflict as a β€œfork”. When a fork happens, each node regards the chain having the highest sum of the PoW answers difficulty as correct. Hence, each node keeps the blockchain that spent the largest computational power in the network. Additionally, when an
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Attack Incentive and Security of Exchanging Tokens on Proof of Work Blockchain
145
attacker rewrites a previous transaction and tries to remake blocks until the last one, at the same time honest nodes are making new blocks that connect the last one. Hence, honest nodes typically choose blocks that were made by honest miners. To succeed in an attack, attackers need to make blocks the fastest in the network by spending computational power larger than honest ones. In other words, the attacker needs over 50% of computational power in the network for sure to succeed. The attack of getting m
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Attack Incentive and Security of Exchanging Tokens on Proof of Work Blockchain
146
attacker rewrites a previous transaction and tries to remake blocks until the last one, at the same time honest nodes are making new blocks that connect the last one. Hence, honest nodes typically choose blocks that were made by honest miners. To succeed in an attack, attackers need to make blocks the fastest in the network by spending computational power larger than honest ones. In other words, the attacker needs over 50% of computational power in the network for sure to succeed. The attack of getting m
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Attack Incentive and Security of Exchanging Tokens on Proof of Work Blockchain
147
ore than 50% computational power is called the β€œ50% attack.” The assumption that a blockchain is secure because double-spending by rewriting does not happen is guaranteed by the difficulty of getting 50% computational power and the difference between the attack cost and the profit. To motivate nodes to make blocks, the system rewards some cryptocurrencies to the maker who succeeds in making a block. In Bitcoin, the system allows block maker to insert a β€œcoinbase transaction” that pays maker some bitcoins
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Attack Incentive and Security of Exchanging Tokens on Proof of Work Blockchain
148
in the block. This mechanism looks like mining gold by spending costs, so making a block by solving PoW is called β€œmining”, and block maker is called β€œminer.” SUB-SECTION: TOKEN EXCHANGE ON BLOCKCHAIN Instead of cryptocurrencies, There are several proposals that manage the rights of tokens control(e.g., a physical asset like lands, digital on
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Attack Incentive and Security of Exchanging Tokens on Proof of Work Blockchain
149
in the block. This mechanism looks like mining gold by spending costs, so making a block by solving PoW is called β€œmining”, and block maker is called β€œminer.” SUB-SECTION: TOKEN EXCHANGE ON BLOCKCHAIN Instead of cryptocurrencies, There are several proposals that manage the rights of tokens control(e.g., a physical asset like lands, digital on
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Attack Incentive and Security of Exchanging Tokens on Proof of Work Blockchain
150
Analysis of the XRP Ledger Consensus Protocol Brad Chase Ethan MacBrough Ripple Research {bchase,emacbrough}@ripple.com February 21, 2018 Abstract The XRP Ledger Consensus Protocol is a previously developed con- sensus protocol powering the XRP Ledger. It is a low-latency Byzantine agreement protocol, capable of reaching consensus without full agreement on which nodes are members of the network. We present a detailed expla- nation of the algorithm and derive conditions for its safety and livenes
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Analysis of the XRP Ledger Consensus Protocol
151
Analysis of the XRP Ledger Consensus Protocol Brad Chase Ethan MacBrough Ripple Research {bchase,emacbrough}@ripple.com February 21, 2018 Abstract The XRP Ledger Consensus Protocol is a previously developed con- sensus protocol powering the XRP Ledger. It is a low-latency Byzantine agreement protocol, capable of reaching consensus without full agreement on which nodes are members of the network. We present a detailed expla- nation of the algorithm and derive conditions for its safety and livenes
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Analysis of the XRP Ledger Consensus Protocol
152
s. 1 Introduction The XRP Ledger is a distributed payment system enabling users to transfer value seamlessly around the world. Operating within a distributed peer-to-peer network, the XRP Ledger faces the same challenges as other digital currencies in preventing double-spending of funds and ensuring network-wide consensus on the state of user accounts and balances. First proposed and then implemented by Schwartz et al. [10], the algorithm underlying XRP solves these problems using a Byzantine fault tole
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Analysis of the XRP Ledger Consensus Protocol
153
s. 1 Introduction The XRP Ledger is a distributed payment system enabling users to transfer value seamlessly around the world. Operating within a distributed peer-to-peer network, the XRP Ledger faces the same challenges as other digital currencies in preventing double-spending of funds and ensuring network-wide consensus on the state of user accounts and balances. First proposed and then implemented by Schwartz et al. [10], the algorithm underlying XRP solves these problems using a Byzantine fault tole
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Analysis of the XRP Ledger Consensus Protocol
154
rant agreement protocol over collectively trusted subnetworks, hereby referred to as the XRP Ledger Consensus Protocol, or XRP LCP for short. Abstractly, the XRP Ledger network is a replicated state machine [9]. The replicated state is the ledger maintained by each node in the network and state transitions correspond to transactions submitted by clients of the network. Once nodes agree on sets of transactions to apply to the state, a transaction processing protocol specifies deterministic rules for order
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Analysis of the XRP Ledger Consensus Protocol
155
rant agreement protocol over collectively trusted subnetworks, hereby referred to as the XRP Ledger Consensus Protocol, or XRP LCP for short. Abstractly, the XRP Ledger network is a replicated state machine [9]. The replicated state is the ledger maintained by each node in the network and state transitions correspond to transactions submitted by clients of the network. Once nodes agree on sets of transactions to apply to the state, a transaction processing protocol specifies deterministic rules for order
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Analysis of the XRP Ledger Consensus Protocol
156
ing transactions within each set and how to apply transactions to generate the new ledger state. Thus, the role of XRP LCP is only to make the network reach agreement on sets of transactions, not on the content or outcome of those transactions. As long as nodes agree on a transaction set, the transaction processing protocol guarantees that every node generates a consistent ledger. As a Byzantine fault tolerant protocol, XRP LCP must operate even in the presence of faulty or malicious participants. Byzant
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Analysis of the XRP Ledger Consensus Protocol
157
ing transactions within each set and how to apply transactions to generate the new ledger state. Thus, the role of XRP LCP is only to make the network reach agreement on sets of transactions, not on the content or outcome of those transactions. As long as nodes agree on a transaction set, the transaction processing protocol guarantees that every node generates a consistent ledger. As a Byzantine fault tolerant protocol, XRP LCP must operate even in the presence of faulty or malicious participants. Byzant
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Analysis of the XRP Ledger Consensus Protocol
158
ine fault tolerant consensus protocols have a rich history, but most require preexisting agreement on the protocol participants [8, 3]. The distin- guishing characteristic of XRP LCP is that it guarantees consistency with only 1 http://arxiv.org/abs/1802.07242v1 partial agreement on who participates, allowing a decentralized open network. Compared to other decentralized consensus algorithms like proof-of-work [7] or proof-of-stake [2], XRP LCP has since its inception provided lower transaction latency
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Analysis of the XRP Ledger Consensus Protocol
159
ine fault tolerant consensus protocols have a rich history, but most require preexisting agreement on the protocol participants [8, 3]. The distin- guishing characteristic of XRP LCP is that it guarantees consistency with only 1 http://arxiv.org/abs/1802.07242v1 partial agreement on who participates, allowing a decentralized open network. Compared to other decentralized consensus algorithms like proof-of-work [7] or proof-of-stake [2], XRP LCP has since its inception provided lower transaction latency
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Analysis of the XRP Ledger Consensus Protocol
160
and higher throughput for its users. However, without uniform agree- ment on the network participants, users still need a way to determine whether their choice of network peers will lead to a consistent network state. In this setting, each user individually defines a unique node list or UNL, which is the set of nodes whose messages it will listen to when making decisions about the network state. It is the intersection of any pair of correct nodes' UNLs that determines network safety. As described in the
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Analysis of the XRP Ledger Consensus Protocol
161
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Analysis of the XRP Ledger Consensus Protocol
162
original whitepaper [10], the minimum overlap requirement was originally believed to be roughly 20% of the UNL. An independent analysis later suggested the correct bound was instead roughly > 40% [1]. Given this confusion, our goal in this work is to give a clear and detailed explanation of XRP LCP and derive the necessary conditions on UNL overlap for consistency and liveness. We will not discuss the transactional semantics of XRP's ledger or XRP's benefits as a digital currency, but instead view the al
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Analysis of the XRP Ledger Consensus Protocol
163
original whitepaper [10], the minimum overlap requirement was originally believed to be roughly 20% of the UNL. An independent analysis later suggested the correct bound was instead roughly > 40% [1]. Given this confusion, our goal in this work is to give a clear and detailed explanation of XRP LCP and derive the necessary conditions on UNL overlap for consistency and liveness. We will not discuss the transactional semantics of XRP's ledger or XRP's benefits as a digital currency, but instead view the al
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Analysis of the XRP Ledger Consensus Protocol
164
gorithm as a general consensus protocol. We re-evaluate the two prior overlap results and provide a single corrected bound which is partway between the bounds of [10] and [1]. We also show that under a more general fault model which was not considered in the original whitepaper but is canonically used in the research literature, the minimum overlap is actually roughly > 90% of the UNL. Finally, we show that during the present stages of diversifying trusted network operators [12], the XRP network is both s
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Analysis of the XRP Ledger Consensus Protocol
165
gorithm as a general consensus protocol. We re-evaluate the two prior overlap results and provide a single corrected bound which is partway between the bounds of [10] and [1]. We also show that under a more general fault model which was not considered in the original whitepaper but is canonically used in the research literature, the minimum overlap is actually roughly > 90% of the UNL. Finally, we show that during the present stages of diversifying trusted network operators [12], the XRP network is both s
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Analysis of the XRP Ledger Consensus Protocol
166
afe and cannot become "stuck" making no forward progress. This research provides a definitive result about the safety of XRP Ledger in its current state. However, to encourage greater flexibility in choosing UNLs in the future, we would prefer an algorithm that gets closer to the original expected overlap bounds. In a sibling paper [6], we present a novel alternative consensus algorithm called Cobalt that lowers the overlap bound to only > 60% in the general fault model, cannot get stuck in any network t
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Analysis of the XRP Ledger Consensus Protocol
167
afe and cannot become "stuck" making no forward progress. This research provides a definitive result about the safety of XRP Ledger in its current state. However, to encourage greater flexibility in choosing UNLs in the future, we would prefer an algorithm that gets closer to the original expected overlap bounds. In a sibling paper [6], we present a novel alternative consensus algorithm called Cobalt that lowers the overlap bound to only > 60% in the general fault model, cannot get stuck in any network t
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Analysis of the XRP Ledger Consensus Protocol
168
hat satisfies the overlap bound, and has several other properties that make it suitable for eventually replacing XRP LCP. This paper thus serves primarily to show that the XRP Ledger is safe in the interim while transitioning to Cobalt, and the relatively strict requirements on UNL configurations under XRP LCP should be viewed in light of this planned transition. Section 2 defines the network model and defines the consensus problem. Sec- tion 3 is a detailed description of the Ripple consensus algorithm.
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Analysis of the XRP Ledger Consensus Protocol
169
hat satisfies the overlap bound, and has several other properties that make it suitable for eventually replacing XRP LCP. This paper thus serves primarily to show that the XRP Ledger is safe in the interim while transitioning to Cobalt, and the relatively strict requirements on UNL configurations under XRP LCP should be viewed in light of this planned transition. Section 2 defines the network model and defines the consensus problem. Sec- tion 3 is a detailed description of the Ripple consensus algorithm.
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Analysis of the XRP Ledger Consensus Protocol
170
In section 4, we prove the network conditions needed to guarantee correctness of the algo- rithm. Finally, section 5 concludes with a discussion of the results and directions for improvement. 2 2 Network Model and Problem Definition Let Pi be a node in the network with unique identifier i, such as a cryptographic public key. Each node Pi is free to choose a unique node list UNLi, which is the set of nodes (possibly including itself) whose messages Pi will listen to as part of the XRP LCP. The UNL re
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Analysis of the XRP Ledger Consensus Protocol
171
In section 4, we prove the network conditions needed to guarantee correctness of the algo- rithm. Finally, section 5 concludes with a discussion of the results and directions for improvement. 2 2 Network Model and Problem Definition Let Pi be a node in the network with unique identifier i, such as a cryptographic public key. Each node Pi is free to choose a unique node list UNLi, which is the set of nodes (possibly including itself) whose messages Pi will listen to as part of the XRP LCP. The UNL re
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Analysis of the XRP Ledger Consensus Protocol
172
presents a subset of the network which, when taken collectively, is trusted by Pi to not collude in an attempt to defraud the network (see [10] for the motivation of this name). The UNLs give structure to the network, with a node that is present in more UNLs implicitly having more influence. An individual node has complete discretion in the choice of their UNL, although we show in section 4 that minimum overlap with other UNLs is necessary for consistency and liveness with other honest nodes. We do not as
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Analysis of the XRP Ledger Consensus Protocol
173
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Analysis of the XRP Ledger Consensus Protocol
174
sume that trust is symmetric, so for instance there may be a node Pj ∈ UNLi such that Pi /∈ UNLj . Figure 1 shows an example trust network. A node that is not crashed and behaves exactly according to the XRP LCP specification is said to be honest or correct; we use the two terms inter- changeably. Any node that does not behave according to protocol is said to be Byzantine. Byzantine behavior can include not responding to messages, sending incorrect messages, and even sending different messages to differe
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Analysis of the XRP Ledger Consensus Protocol
175
sume that trust is symmetric, so for instance there may be a node Pj ∈ UNLi such that Pi /∈ UNLj . Figure 1 shows an example trust network. A node that is not crashed and behaves exactly according to the XRP LCP specification is said to be honest or correct; we use the two terms inter- changeably. Any node that does not behave according to protocol is said to be Byzantine. Byzantine behavior can include not responding to messages, sending incorrect messages, and even sending different messages to differe
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Analysis of the XRP Ledger Consensus Protocol
176
nt parties. In section 4, we initially consider a restriction on the adversary called Byzantine accountability, which states that all nodes – even Byzantine ones – cannot send different messages to different nodes. This was part of the original whitepaper [10], which assumed such behavior in a peer-to-peer network could be identified and corrected by honest nodes. However, due to asynchrony and the possibility of honest nodes being temporarily partitioned, this assumption is in practice tenuous at best. T
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Analysis of the XRP Ledger Consensus Protocol
177
nt parties. In section 4, we initially consider a restriction on the adversary called Byzantine accountability, which states that all nodes – even Byzantine ones – cannot send different messages to different nodes. This was part of the original whitepaper [10], which assumed such behavior in a peer-to-peer network could be identified and corrected by honest nodes. However, due to asynchrony and the possibility of honest nodes being temporarily partitioned, this assumption is in practice tenuous at best. T
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Analysis of the XRP Ledger Consensus Protocol
178
hus the bulk of our results do not depend on this assumption and we will clearly state when it is assumed. For any node Pi, we denote ni = |UNLi| and define the quorum, denoted qi, a parameter which roughly specifies the minimum number of agreeing nodes in UNLi that Pi needs to hear from to commit to a decision. Each node sets qi to be 80% of its UNL size, or, more exactly, qi = ⌈0.8niβŒ‰. We assume at most ti 6 ni βˆ’ qi nodes in UNLi may be Byzantine faulty. Let L represent a ledger, which is the shared s
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Analysis of the XRP Ledger Consensus Protocol
179
hus the bulk of our results do not depend on this assumption and we will clearly state when it is assumed. For any node Pi, we denote ni = |UNLi| and define the quorum, denoted qi, a parameter which roughly specifies the minimum number of agreeing nodes in UNLi that Pi needs to hear from to commit to a decision. Each node sets qi to be 80% of its UNL size, or, more exactly, qi = ⌈0.8niβŒ‰. We assume at most ti 6 ni βˆ’ qi nodes in UNLi may be Byzantine faulty. Let L represent a ledger, which is the shared s
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Analysis of the XRP Ledger Consensus Protocol
180
tate of the system and includes account settings, balances, order books, etc. Two ledgers L,Lβ€² are the same if they represent the same ordered history of transactions starting from the unique genesis ledger. Each ledger also has sequence number seq(L) that is one greater than its parent ledger's sequence number. The genesis ledger has seq(L) = 1. A ledger L is created by applying a sequence of transactions T = [x0, x1, . . .] to its parent parent(L) according to the protocol rules. Two ledgers may have th
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Analysis of the XRP Ledger Consensus Protocol
181
tate of the system and includes account settings, balances, order books, etc. Two ledgers L,Lβ€² are the same if they represent the same ordered history of transactions starting from the unique genesis ledger. Each ledger also has sequence number seq(L) that is one greater than its parent ledger's sequence number. The genesis ledger has seq(L) = 1. A ledger L is created by applying a sequence of transactions T = [x0, x1, . . .] to its parent parent(L) according to the protocol rules. Two ledgers may have th
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Analysis of the XRP Ledger Consensus Protocol
182
e same parent ledger and sequence number, but differ because they applied different transactions. Note though that the protocol specifies that every set of transactions has a deterministic ordering, so it is not possible for two correct nodes to apply the same transactions but in a different order. The nodes communicate over a peer-to-peer network which has no prescribed relation with the UNL structure. We simply assume that for every node Pi and every node Pj ∈ UNLi, there is a reliable authenticated ch
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Analysis of the XRP Ledger Consensus Protocol
183
e same parent ledger and sequence number, but differ because they applied different transactions. Note though that the protocol specifies that every set of transactions has a deterministic ordering, so it is not possible for two correct nodes to apply the same transactions but in a different order. The nodes communicate over a peer-to-peer network which has no prescribed relation with the UNL structure. We simply assume that for every node Pi and every node Pj ∈ UNLi, there is a reliable authenticated ch
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Analysis of the XRP Ledger Consensus Protocol
184
annel for Pi to receive 3 a c b e d g f i h j Figure 1: Example trust graph. The highlighted edges represent the UNL of node Pi. messages from Pj . To implement such an authenticated channel, all messages are cryptographically signed and verified by receivers. Each node uses a single communication primitive broadcast, which when called from node Pj sends the same message to all nodes Pi for which Pj ∈ UNLi. In the algorithms presented in appendix A, we use a corresponding receive primitive
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Analysis of the XRP Ledger Consensus Protocol
185
annel for Pi to receive 3 a c b e d g f i h j Figure 1: Example trust graph. The highlighted edges represent the UNL of node Pi. messages from Pj . To implement such an authenticated channel, all messages are cryptographically signed and verified by receivers. Each node uses a single communication primitive broadcast, which when called from node Pj sends the same message to all nodes Pi for which Pj ∈ UNLi. In the algorithms presented in appendix A, we use a corresponding receive primitive
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Analysis of the XRP Ledger Consensus Protocol
186
which is called asynchronously upon the receipt of a broadcast message. The outcome of XRP LCP is for a node to fully validate ledgers. A fully validated ledger is irrevocable and authoritative, and reflects transactions sub- mitted by network clients and accepted by the consensus algorithm. Fully vali- dating a ledger also fully validates all of its ancestors. In this context, a fork is a situation in which two honest nodes fully validate contradictory ledgers, i.e., different ledgers with the same sequ
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Analysis of the XRP Ledger Consensus Protocol
187
which is called asynchronously upon the receipt of a broadcast message. The outcome of XRP LCP is for a node to fully validate ledgers. A fully validated ledger is irrevocable and authoritative, and reflects transactions sub- mitted by network clients and accepted by the consensus algorithm. Fully vali- dating a ledger also fully validates all of its ancestors. In this context, a fork is a situation in which two honest nodes fully validate contradictory ledgers, i.e., different ledgers with the same sequ
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Analysis of the XRP Ledger Consensus Protocol
188
ence number. The network is said to be fork-safe if it can never fork with a tolerated configuration of Byzantine nodes. Although XRP LCP is typically defined in terms of the fully validated chain of ledgers, since each ledger in the chain represents a deterministically-ordered sequence of transactions it also can be considered as an atomic broadcast pro- tocol with batching of transactions for efficiency. Formally, an atomic broadcast protocol is an algorithm in which a set of clients, arbitrarily many
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Analysis of the XRP Ledger Consensus Protocol
189
ence number. The network is said to be fork-safe if it can never fork with a tolerated configuration of Byzantine nodes. Although XRP LCP is typically defined in terms of the fully validated chain of ledgers, since each ledger in the chain represents a deterministically-ordered sequence of transactions it also can be considered as an atomic broadcast pro- tocol with batching of transactions for efficiency. Formally, an atomic broadcast protocol is an algorithm in which a set of clients, arbitrarily many
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Analysis of the XRP Ledger Consensus Protocol
190
of which may be Byzantine faulty, can broadcast transactions, and each node can accept some of those transactions according to the following properties: 1. ABC-Agreement: If a correct node accepts a transaction into a ledger, then eventually all correct nodes accept the transaction into a ledger. 4 2. ABC-Linearizability: If a correct node accepts transaction x before trans- action xβ€², then all correct nodes accept transaction x before xβ€². 3. ABC-Censorship-Resilience: If a correct client broadcast
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Analysis of the XRP Ledger Consensus Protocol
191
of which may be Byzantine faulty, can broadcast transactions, and each node can accept some of those transactions according to the following properties: 1. ABC-Agreement: If a correct node accepts a transaction into a ledger, then eventually all correct nodes accept the transaction into a ledger. 4 2. ABC-Linearizability: If a correct node accepts transaction x before trans- action xβ€², then all correct nodes accept transaction x before xβ€². 3. ABC-Censorship-Resilience: If a correct client broadcast
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Analysis of the XRP Ledger Consensus Protocol
192
s a valid transac- tion x to all correct nodes, x will eventually be accepted by all nodes. An atomic broadcast algorithm is in particular a variant of consensus [4]. Note that Censorship Resilience is the formalized definition of forward progress. In practice, the peer-to-peer network weakens the requirement that clients sub- mit their transaction to all correct nodes, since correct nodes will echo a sub- mitted transaction to each other, flooding the network until every node receives it. In order to e
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Analysis of the XRP Ledger Consensus Protocol
193
s a valid transac- tion x to all correct nodes, x will eventually be accepted by all nodes. An atomic broadcast algorithm is in particular a variant of consensus [4]. Note that Censorship Resilience is the formalized definition of forward progress. In practice, the peer-to-peer network weakens the requirement that clients sub- mit their transaction to all correct nodes, since correct nodes will echo a sub- mitted transaction to each other, flooding the network until every node receives it. In order to e
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Analysis of the XRP Ledger Consensus Protocol
194
valuate the correctness of XRP LCP, we model the peer-to- peer network as if it were controlled by a network adversary that can behave arbitrarily. The adversary is controls the delivery order of all messages, as well as at most ti nodes in UNLi for any correct node Pi. We assume though that the adversary is computationally bounded; in particular, it is unable to break generally accepted cryptographic protocols. The identities of Byzantine nodes are unknown in advance by honest nodes in the network. Sinc
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Analysis of the XRP Ledger Consensus Protocol
195
valuate the correctness of XRP LCP, we model the peer-to- peer network as if it were controlled by a network adversary that can behave arbitrarily. The adversary is controls the delivery order of all messages, as well as at most ti nodes in UNLi for any correct node Pi. We assume though that the adversary is computationally bounded; in particular, it is unable to break generally accepted cryptographic protocols. The identities of Byzantine nodes are unknown in advance by honest nodes in the network. Sinc
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Analysis of the XRP Ledger Consensus Protocol
196
e atomic broadcast is a variant of consensus, by the FLP result [5] we cannot guarantee forward progress in the presence of arbitrary asynchrony and faulty nodes. Instead, we assume a form of "weak asynchrony": safety should hold under arbitrary asynchrony, but censorship resilience is only guaranteed to hold under the assumption that the network is eventually civil, meaning that messages are delivered within some protocol-specified maximum delay bound and no nodes are faulty. In order to help enforce th
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Analysis of the XRP Ledger Consensus Protocol
197
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Analysis of the XRP Ledger Consensus Protocol
198
e bounded delay in the XRP ledger implemen- tation, several heuristics are used to identify lagging nodes, prevent excessive flooding of messages and route traffic through the network. Protocol parameters also define maximum delays on different trusted messages in an attempt to aid liveness. Although we ignore these details to simplify the presentation below, we stress that they are important practical considerations in the actual implemen- tation and control the real world performance of the algorithm. T
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Analysis of the XRP Ledger Consensus Protocol
199