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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
200
he fact that XRP LCP is only weakly asynchronous and its performance depends on these parameters is a limitation of the algorithm. Cobalt, the proposed alternative algorithm to XRP LCP, does not have these limitations. It uses cryptographic randomness to evade the FLP result and guarantees forward progress even with the maximal number of tolerated faulty nodes and unbounded asynchrony [6]. Table 1 summarizes our notation, including some that will be explained in subsequent sections. 3 The XRP Ledger Con
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Analysis of the XRP Ledger Consensus Protocol
201
he fact that XRP LCP is only weakly asynchronous and its performance depends on these parameters is a limitation of the algorithm. Cobalt, the proposed alternative algorithm to XRP LCP, does not have these limitations. It uses cryptographic randomness to evade the FLP result and guarantees forward progress even with the maximal number of tolerated faulty nodes and unbounded asynchrony [6]. Table 1 summarizes our notation, including some that will be explained in subsequent sections. 3 The XRP Ledger Con
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Analysis of the XRP Ledger Consensus Protocol
202
sensus Protocol The XRP Ledger Consensus Protocol consists of three primary components: • Deliberation, in which nodes iteratively propose a transaction set to apply to a prior ledger, based on proposals received from other trusted 5 Pi A node in the network UNLi The unique node list (UNL) selected by Pi ni, qi, ti The size, validation quorum and maximum Byzantine faults of UNLi L A ledger seq(L) Sequence number of ledger L L̂ Fully validated ledger with largest sequence number (the fully validat
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Analysis of the XRP Ledger Consensus Protocol
203
sensus Protocol The XRP Ledger Consensus Protocol consists of three primary components: • Deliberation, in which nodes iteratively propose a transaction set to apply to a prior ledger, based on proposals received from other trusted 5 Pi A node in the network UNLi The unique node list (UNL) selected by Pi ni, qi, ti The size, validation quorum and maximum Byzantine faults of UNLi L A ledger seq(L) Sequence number of ledger L L̂ Fully validated ledger with largest sequence number (the fully validat
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Analysis of the XRP Ledger Consensus Protocol
204
ed tip ledger) L̃ Current working ledger of deliberation T = {x0, x1, . . .} A set of transactions PT,r,L,i Node Pi's r-th deliberation proposal of transactions T to apply to L VL,i Node Pi's validation of ledger L supptip(L), suppbranch(L) Tip and branch support of a ledger L uncommitted(s) Uncommitted support at sequence number s φ(L,L′) Ordering function that is 1 if L > L′ (by hash) and 0 otherwise Table 1: Summary of notation nodes. When a node believes enough proposals agree, it applies the cor
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Analysis of the XRP Ledger Consensus Protocol
205
ed tip ledger) L̃ Current working ledger of deliberation T = {x0, x1, . . .} A set of transactions PT,r,L,i Node Pi's r-th deliberation proposal of transactions T to apply to L VL,i Node Pi's validation of ledger L supptip(L), suppbranch(L) Tip and branch support of a ledger L uncommitted(s) Uncommitted support at sequence number s φ(L,L′) Ordering function that is 1 if L > L′ (by hash) and 0 otherwise Table 1: Summary of notation nodes. When a node believes enough proposals agree, it applies the cor
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Analysis of the XRP Ledger Consensus Protocol
206
re- sponding transactions to the prior ledger according to the ledger protocol rules. It then issues a validation for the generated ledger. • Validation, in which nodes decide whether to fully validate a ledger, based on the validations issued by trusted nodes. Once a quorum of val- idations for the same ledger is reached, that le
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Analysis of the XRP Ledger Consensus Protocol
207
re- sponding transactions to the prior ledger according to the ledger protocol rules. It then issues a validation for the generated ledger. • Validation, in which nodes decide whether to fully validate a ledger, based on the validations issued by trusted nodes. Once a quorum of val- idations for the same ledger is reached, that le
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Analysis of the XRP Ledger Consensus Protocol
208
Abstract -The censorship attack is ubiquitous in prevailing blockchains, such as Bitcoin and Ethereum, yet has not been resolved well so far. According to known vulnerabilities of different consensus algorithms, censorship attacks can always achieve great benefits at low costs by various means. In this paper, we propose improvements to existing POS and POW algorithms to resolve censorship attacks in two methods. The first method improves the Tendermint consensus mechanism by introducing three new types o
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Improved consensus mechanisms against censorship attacks
209
Abstract -The censorship attack is ubiquitous in prevailing blockchains, such as Bitcoin and Ethereum, yet has not been resolved well so far. According to known vulnerabilities of different consensus algorithms, censorship attacks can always achieve great benefits at low costs by various means. In this paper, we propose improvements to existing POS and POW algorithms to resolve censorship attacks in two methods. The first method improves the Tendermint consensus mechanism by introducing three new types o
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Improved consensus mechanisms against censorship attacks
210
f messages and an auxiliary role of network nodes. The method can automatically defend against censorship attacks and organize an honest chain. The second method is based on the CasperFFG consensus mechanism and can accurately identify the attackers by evaluating the suspicious scores of all validators. However, an honest validator has to manually choose the honest chain. Theoretical analyses show their effectiveness. - Keywords — Blockchain, Protocol Security, Censorship Attack, Consensus Mechanism
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Improved consensus mechanisms against censorship attacks
211
f messages and an auxiliary role of network nodes. The method can automatically defend against censorship attacks and organize an honest chain. The second method is based on the CasperFFG consensus mechanism and can accurately identify the attackers by evaluating the suspicious scores of all validators. However, an honest validator has to manually choose the honest chain. Theoretical analyses show their effectiveness. - Keywords — Blockchain, Protocol Security, Censorship Attack, Consensus Mechanism
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Improved consensus mechanisms against censorship attacks
212
I. INTRODUCTION The security is critical for the current blockchain systems, which are suffering from various vulnerabilities at various levels, from the entire system to all modules, such as the consensus algorithm. Certain vulnerabilities are implicit at the program level, which are easy to fix once discovered. Certain vulnerabilities are explicit at the protocol level, which are difficult t
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Improved consensus mechanisms against censorship attacks
213
I. INTRODUCTION The security is critical for the current blockchain systems, which are suffering from various vulnerabilities at various levels, from the entire system to all modules, such as the consensus algorithm. Certain vulnerabilities are implicit at the program level, which are easy to fix once discovered. Certain vulnerabilities are explicit at the protocol level, which are difficult t
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Improved consensus mechanisms against censorship attacks
214
Albatross An optimistic consensus algorithm Version 4 – December 10, 2019 Bruno França Nimiq Foundation [email protected] Marvin Wissfeld Nimiq Foundation [email protected] Pascal Berrang Nimiq Foundation [email protected] Philipp von Styp-Rekowsky Nimiq Foundation [email protected] Abstract—The area of distributed ledgers is a vast and quickly developing landscape. At the heart of most distributed ledgers is their consensus protocol. The consensus protocol describes the way participants in a distri
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Albatross An optimistic consensus algorithm
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Albatross An optimistic consensus algorithm Version 4 – December 10, 2019 Bruno França Nimiq Foundation [email protected] Marvin Wissfeld Nimiq Foundation [email protected] Pascal Berrang Nimiq Foundation [email protected] Philipp von Styp-Rekowsky Nimiq Foundation [email protected] Abstract—The area of distributed ledgers is a vast and quickly developing landscape. At the heart of most distributed ledgers is their consensus protocol. The consensus protocol describes the way participants in a distri
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Albatross An optimistic consensus algorithm
216
buted network interact with each other to obtain and agree on a shared state. While classical consensus Byzantine fault tolerant (BFT) algorithms are designed to work in closed, size-limited networks only, modern distributed ledgers – and blockchains in particular – often focus on open, permissionless networks. In this paper, we present a novel blockchain consensus algo- rithm, called Albatross, inspired by speculative BFT algorithms. Transactions in Albatross benefit from strong probabilistic final- ity
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Albatross An optimistic consensus algorithm
217
. We describe the technical specification of Albatross in detail and analyse its security and performance. We conclude that the protocol is secure under regular PBFT security assumptions and has a performance close to the theoretical maximum for single- chain Proof-of-Stake consensus algorithms. I. INTRODUCTION The most famous classical consensus algorithm is PBFT, or practical Byzantine fault tolerance [1]. PBFT has greatly influenced the field since its creation in 1999 and is now a major component in
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Albatross An optimistic consensus algorithm
218
many of the consensus algorithms being used or developed for blockchains. However, classical consensus theory has evolved significantly and, nowadays, the BFT algorithms providing the highest performance are speculative BFT algorithms. Speculative BFT refers to a class of algorithms that have two modes for consensus: (1) the optimistic mode, where it is assumed that the nodes are well-behaved and so little security measures are applied, instead preferring speed, and (2) the pessimistic mode, where no su
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Albatross An optimistic consensus algorithm
219
many of the consensus algorithms being used or developed for blockchains. However, classical consensus theory has evolved significantly and, nowadays, the BFT algorithms providing the highest performance are speculative BFT algorithms. Speculative BFT refers to a class of algorithms that have two modes for consensus: (1) the optimistic mode, where it is assumed that the nodes are well-behaved and so little security measures are applied, instead preferring speed, and (2) the pessimistic mode, where no su
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Albatross An optimistic consensus algorithm
220
ch assumption is made and the only goal is to make progress even in the presence of malicious nodes. The reason for speculative BFT algorithms being signifi- cantly faster than non-speculative versions lies in the opti- mistic mode, which allows them to compete with centralized systems in terms of speed. The optimistic mode, however, is not robust or safe at all, with any node being able to make an invalid update. When that happens, speculative BFT algorithms automatically enter into pessimistic mode, re
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Albatross An optimistic consensus algorithm
221
ch assumption is made and the only goal is to make progress even in the presence of malicious nodes. The reason for speculative BFT algorithms being signifi- cantly faster than non-speculative versions lies in the opti- mistic mode, which allows them to compete with centralized systems in terms of speed. The optimistic mode, however, is not robust or safe at all, with any node being able to make an invalid update. When that happens, speculative BFT algorithms automatically enter into pessimistic mode, re
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Albatross An optimistic consensus algorithm
222
vert the invalid update and then change back into optimistic mode. This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 International License. The idea here is deceptively simple. In PBFT, the nodes adopt a "never trust" attitude, all updates to the ledger being carried out with a focus on maximum security. In speculative BFT, the nodes adopt a "trust but verify" attitude, being allowed to make an update by themselves but with other nodes verifying the update afterwards and it bei
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Albatross An optimistic consensus algorithm
223
ng reverted if it is not valid. Albatross, our novel blockchain 1 consensus algorithm, is modeled after some of these speculative BFT algorithms like Zyzzyva [2], but it also takes inspiration from other consensus algorithms like Byzcoin [3], Algorand [4] and Bitcoin-NG [5]. II. OVERVIEW In this section, we will give a summary of Albatross, de- scribing in an intuitive fashion the different types of validators, blocks and the chain selection algorithm. We also present the behavior of the protocol in th
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Albatross An optimistic consensus algorithm
224
ng reverted if it is not valid. Albatross, our novel blockchain 1 consensus algorithm, is modeled after some of these speculative BFT algorithms like Zyzzyva [2], but it also takes inspiration from other consensus algorithms like Byzcoin [3], Algorand [4] and Bitcoin-NG [5]. II. OVERVIEW In this section, we will give a summary of Albatross, de- scribing in an intuitive fashion the different types of validators, blocks and the chain selection algorithm. We also present the behavior of the protocol in th
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Albatross An optimistic consensus algorithm
225
e optimistic mode, discuss the ways validators may misbehave and how such misbehavior is countered in our protocol. We will focus on the general structure of Albatross and leave the details for Section IV. A. Validators There are two types of validators: potential and active validators. A potential validator is any node that has staked tokens (i.e., tokens that are locked away for this purpose), so that it can be selected for block production. An active validator is a potential validator that was selec
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Albatross An optimistic consensus algorithm
226
e optimistic mode, discuss the ways validators may misbehave and how such misbehavior is countered in our protocol. We will focus on the general structure of Albatross and leave the details for Section IV. A. Validators There are two types of validators: potential and active validators. A potential validator is any node that has staked tokens (i.e., tokens that are locked away for this purpose), so that it can be selected for block production. An active validator is a potential validator that was selec
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Albatross An optimistic consensus algorithm
227
ted to produce blocks during the current epoch and thus has an active role. The set of all potential and active validators is called the validator set. The list of active validators tasked to produce blocks during a given epoch is called the validator list. Simi- larly to other hybrid consensus algorithms, the validator list is chosen at random from the validator set, and the probability of a validator being chosen is proportional to its stake. Any given validator can appear more than once in the validat
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Albatross An optimistic consensus algorithm
228
or list, but only appears exactly one time in the validator set. 1It is important to note that we focus on a cryptocurrency use case here. We assume that blocks contain transactions and that the underlying token has a monetary value. 1 ar X iv :1 90 3. 01 58 9v 3 [ cs .C R ] 1 4 Ja n 20 20 B. Blocks There are two types of blocks that are produced by the validators: • Macro blocks: These blocks are used to change the validator list and contain the identities of the new active valida
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Albatross An optimistic consensus algorithm
229
or list, but only appears exactly one time in the validator set. 1It is important to note that we focus on a cryptocurrency use case here. We assume that blocks contain transactions and that the underlying token has a monetary value. 1 ar X iv :1 90 3. 01 58 9v 3 [ cs .C R ] 1 4 Ja n 20 20 B. Blocks There are two types of blocks that are produced by the validators: • Macro blocks: These blocks are used to change the validator list and contain the identities of the new active valida
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Albatross An optimistic consensus algorithm
230
tors. They do not contain user-generated transac- tions. Macro blocks are produced with PBFT. • Micro blocks: These blocks are the ones that contain user-generated transactions. Each micro block is pro- duced by a randomly chosen active validator and contains not only the transactions to be included, but also the current state and a random seed produced by the validator. Micro blocks only need to be signed by the corresponding elected validator. One macro block is always followed by m micro blocks, with
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Albatross An optimistic consensus algorithm
231
this pattern repeating throughout the blockchain. An epoch is composed of a macro block and the m micro blocks that preceded it. C. Chain selection Nodes will believe the longest chain, by number of blocks, to be the main chain. Note that, since macro blocks have finality and are thus forkless, any fork can only happen between two macro blocks. So, nodes only need to consider chains that include the last macro block. D. Optimistic mode Now, we will consider what happens during an epoch in Albatross,
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Albatross An optimistic consensus algorithm
232
this pattern repeating throughout the blockchain. An epoch is composed of a macro block and the m micro blocks that preceded it. C. Chain selection Nodes will believe the longest chain, by number of blocks, to be the main chain. Note that, since macro blocks have finality and are thus forkless, any fork can only happen between two macro blocks. So, nodes only need to consider chains that include the last macro block. D. Optimistic mode Now, we will consider what happens during an epoch in Albatross,
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Albatross An optimistic consensus algorithm
233
assuming that all validators are honest. We call this the optimistic mode because we are trusting that the validators will not misbehave. 1) At the beginning of an epoch a new validator list is cho- sen at random. The validators are chosen proportionally to their stake from the validator set. 2) Using a random seed, a validator is selected at random to produce the next micro block. This validator is called the slot owner. 3) The slot owner chooses which transactions to include in the block and calculat
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Albatross An optimistic consensus algorithm
234
es the resulting state. He also produces a new random seed that will be used to select the slot owner for the next block. 4) He includes the transactions, the current state, and the random seed in the block, signs it and relays it. 5) Now the next slot owner repeats the process and pro- duces another micro block that appends some transac- tions to the blockchain and picks the next slot owner. This continues until the last micro block in the current epoch, which will pick the validator that will be PBFT
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Albatross An optimistic consensus algorithm
235
leader for the macro block. 6) The PBFT leader will also produce a new random seed which will be used to select a new validator list for the next epoch. However, there are no transactions to include in the block. 7) The leader and the other validators sign the block and relay it. Note that the validators will produce their random seeds using a verifiable random function. A verifiable random func- tion is a pseudo-random function that cannot be manipulated by the validator and so guarantees a fair selec
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Albatross An optimistic consensus algorithm
236
tion. E. Misbehaving validators The protocol above constitutes the optimistic case, assuming honest validators. However, Albatross also needs to be able to withstand malicious validators. To this end, we present appropriate measures for the three ways in which a validator can misbehave: producing an invalid block, creating a fork, and delaying a block. 1) Forks: Forks are not possible during a macro block, because PBFT is a forkless protocol. But a fork can be created if a validator produces more than
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Albatross An optimistic consensus algorithm
237
tion. E. Misbehaving validators The protocol above constitutes the optimistic case, assuming honest validators. However, Albatross also needs to be able to withstand malicious validators. To this end, we present appropriate measures for the three ways in which a validator can misbehave: producing an invalid block, creating a fork, and delaying a block. 1) Forks: Forks are not possible during a macro block, because PBFT is a forkless protocol. But a fork can be created if a validator produces more than
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Albatross An optimistic consensus algorithm
238
one micro block in the same slot. To deal with this, we introduce fork proofs. Anyone can create a fork proof. Two block headers, at the same slot, signed by the same validator, constitute sufficient proof. If a malicious validator creates or continues a fork, even- tually an honest validator will produce a block containing a fork proof and the malicious validator will be punished. 2) Delays: Validators can potentially take a long time to produce a block, either because they went offline or because they
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Albatross An optimistic consensus algorithm
239
maliciously try to delay the block production. In both cases, we need to change the slot owner. To this end, we use the view change protocol of PBFT. After receiving a block, each validator starts a countdown. If he doesn't receive the next block before the timer ends, he sends out a message requesting a view change (a change of the slot owner). Any validator that receives such messages from at least two-thirds of the validator list, will no longer accept a block from the current slot owner. Instead, a
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Albatross An optimistic consensus algorithm
240
new slot owner is chosen to produce a block and a new countdown begins. The new slot owner is chosen in the following way. The random seed and a counter are hashed together to produce a random value that is used to pick a validator from the validator list. By increasing the counter, we can create an ordered list of slot owners. If the first slot owner does not produce a block in time, the second slot owner is selected to produce the block. If the second slot owner also fails to produce a block, the third
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Albatross An optimistic consensus algorithm
241
slot owner is selected and so on. 3) Invalid blocks: When a validator produces an invalid block, either when he is the slot owner for a micro block or the PBFT leader for a macro block, the other validators just need to ignore that block. 4) Punishment: Validators that fork or delay blocks are punished in the same way: they get banned from producing any more micro blocks during the current epoch and their reward for the whole epoch is burned. Moreover, such validators are marked to be automatically rem
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Albatross An optimistic consensus algorithm
242
oved from the registry of potential validators if they do not prove being active within two epochs. III. PRELIMINARIES A. Practical Byzantine Fault Tolerance The practical Byzantine fault tolerance consensus algorithm, or PBFT for short, was introduced by Castro and Liskov in 2 1999 [1]. Assuming that there are 3f + 1 nodes, PBFT can tolerate up to f faults and, thus, is optimal for a partially synchronous BFT protocol. There are several slightly different variants of PBFT but we will only describe
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Albatross An optimistic consensus algorithm
243
oved from the registry of potential validators if they do not prove being active within two epochs. III. PRELIMINARIES A. Practical Byzantine Fault Tolerance The practical Byzantine fault tolerance consensus algorithm, or PBFT for short, was introduced by Castro and Liskov in 2 1999 [1]. Assuming that there are 3f + 1 nodes, PBFT can tolerate up to f faults and, thus, is optimal for a partially synchronous BFT protocol. There are several slightly different variants of PBFT but we will only describe
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Albatross An optimistic consensus algorithm
244
the one used in Albatross. PBFT proceeds in four rounds: • Pre-prepare: In this phase, the leader multicasts a block proposal to the rest of the validator list. • Prepare: After receiving the block proposal, each valida- tor determines if it is valid. If it is, he calculates the block hash h and signs a message saying 〈PREPARE, h〉. Then, he multicasts the signature to the rest of the validator list. The leader also sends a prepare message. • Commit: If a validator receives prepare messages from at le
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Albatross An optimistic consensus algorithm
245
ast 2f + 1 validators, he signs a message saying 〈COMMIT, h〉 and multicasts it to the rest of the validator list. • Reply: If a validator receives 2f + 1 commit messages from validators who also sent prepare messages, the block is considered finalized. Then, he gossips the block to the network. Instead of sending all signatures in the block separately, we can save space by aggregating them. This way all the prepare messages are aggregated into a single signature and a bitmap is created stating which val
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Albatross An optimistic consensus algorithm
246
idators sent prepare messages. The exact same is done to the commit messages. So the justification for the block consists just of the two aggregated signatures and the corresponding bitmaps. B. Boneh-Lynn-Shacham signatures Boneh-Lynn-Shacham (BLS) is a signature scheme that was first introduced in 2004 [6] and uses both elliptic curve cryptography and bilinear pairings. Its security is less con- servative than some other more commonly used digital sig- nature schemes (for example ECDSA and Schnorr), bu
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Albatross An optimistic consensus algorithm
247
t is still considered secure by the majority of the cryptography community. It also offers several advantages over ECDSA and Schnorr, namely: shorter signature sizes, deterministic signatures, and simple schemes for signature aggregation, threshold signatures, and multisignatures. To understand BLS, first it is necessary to understand bilinear pairings. A bilinear pairing is a function that takes two elliptic curves points, possibly in two different curves and outputs a point in another curve. It also mu
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Albatross An optimistic consensus algorithm
248
t is still considered secure by the majority of the cryptography community. It also offers several advantages over ECDSA and Schnorr, namely: shorter signature sizes, deterministic signatures, and simple schemes for signature aggregation, threshold signatures, and multisignatures. To understand BLS, first it is necessary to understand bilinear pairings. A bilinear pairing is a function that takes two elliptic curves points, possibly in two different curves and outputs a point in another curve. It also mu
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Albatross An optimistic consensus algorithm
249
st have the bilinearity property. A more precise definition is: Let G1 and G2 be additive groups of prime order p, and GT be a multiplicative group also of prime order p. Let P ∈ G1 and Q ∈ G2 be generators of G1 and G2, respectively, and a, b ∈ Zp. Then, a bilinear is a map e : G1 × G2 → GT such that e(aP, bQ) = e(P,Q)ab and e(P,Q) 6= 1. For such bilinear pairings, e(aP, bQ) = e(P,Q)ab implies that e(xP,Q) = e(P, xQ). BLS signatures only require a bilinear pairing (with the curves to support it) and a
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Albatross An optimistic consensus algorithm
250
st have the bilinearity property. A more precise definition is: Let G1 and G2 be additive groups of prime order p, and GT be a multiplicative group also of prime order p. Let P ∈ G1 and Q ∈ G2 be generators of G1 and G2, respectively, and a, b ∈ Zp. Then, a bilinear is a map e : G1 × G2 → GT such that e(aP, bQ) = e(P,Q)ab and e(P,Q) 6= 1. For such bilinear pairings, e(aP, bQ) = e(P,Q)ab implies that e(xP,Q) = e(P, xQ). BLS signatures only require a bilinear pairing (with the curves to support it) and a
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Albatross An optimistic consensus algorithm
251
hash function that maps to el- liptic curve points in G1. This hash function is defined as h : M → G1. Given these primitives, the BLS signature scheme is defined as follows: • Key generation: Choose at random an integer x R←− Zp and calculate Y = xQ. The secret key is x and the public key is Y . • Signing: Let m ∈ M be the message. To create a signature, the message needs to be hashed H = h(m). Then, calculate the signature as σ = xH . • Verifying: Given a signature σ and a public key Y , accept the
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Albatross An optimistic consensus algorithm
252
signature if e(σ,Q) = e(H,Y ). As we have said before, BLS has a number of desirable fea- tures. One that is useful for our design is signature aggregation. BLS allows to combine n signatures of n different signers into a single signature thus saving a considerable amount of space. The scheme is as follows: • Setup: Each of the n signers creates a secret key xi and a public key Yi. • Signing: Each of the n signers uses their secret key to create signatures σi. • Aggregation: The aggregated signature
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Albatross An optimistic consensus algorithm
253
signature if e(σ,Q) = e(H,Y ). As we have said before, BLS has a number of desirable fea- tures. One that is useful for our design is signature aggregation. BLS allows to combine n signatures of n different signers into a single signature thus saving a considerable amount of space. The scheme is as follows: • Setup: Each of the n signers creates a secret key xi and a public key Yi. • Signing: Each of the n signers uses their secret key to create signatures σi. • Aggregation: The aggregated signature
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Albatross An optimistic consensus algorithm
254
is simply the sum of all individual signatures σ = ∑n i=1 σi. • Verifying: Calculate the aggregate public key Y =∑n i=1 Yi. Accept the signature σ if e(σ,Q) = e(H,Y ). C. Verifiable Random Functions A verifiable random function is a pseudo-random function that can provide publicly verifiable proofs that its output is correct. More formally, after a user creates a public key Y and a secret key x, given an input s, the user can calculate the VRF π, r = VRFx(s). Here, r is the pseudo-random output and π
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Albatross An optimistic consensus algorithm
255
is simply the sum of all individual signatures σ = ∑n i=1 σi. • Verifying: Calculate the aggregate public key Y =∑n i=1 Yi. Accept the signature σ if e(σ,Q) = e(H,Y ). C. Verifiable Random Functions A verifiable random function is a pseudo-random function that can provide publicly verifiable proofs that its output is correct. More formally, after a user creates a public key Y and a secret key x, given an input s, the user can calculate the VRF π, r = VRFx(s). Here, r is the pseudo-random output and π
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Albatross An optimistic consensus algorithm
256
is a proof for the correct computation of it. Then, anyone who knows the public key and the proof can verify that r was correctly computed, without learning the secret key x. Verifiable random functions have three important properties: • Pseudo-randomness: The only way of predicting the output, better than guessing randomly, is to calculate the function. • Uniqueness: For each input s and secret key x there is only one possible output r. • Public verifiability: Anyone can verify that the output was c
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Albatross An optimistic consensus algorithm
257
orrectly computed. The BLS signature scheme has all these properties with the advantage that the signature serve as both the pseudo-random value and proof of correctness. For this paper we will use we will use BLS signatures as a simple verifiable random function. IV. SPECIFICATION We will now give the technical specification of Albatross, describing in detail the networking, all of the validator's functions and processes, the block's format, the misbehavior handling protocols, the rewards and punishme
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Albatross An optimistic consensus algorithm
258
orrectly computed. The BLS signature scheme has all these properties with the advantage that the signature serve as both the pseudo-random value and proof of correctness. For this paper we will use we will use BLS signatures as a simple verifiable random function. IV. SPECIFICATION We will now give the technical specification of Albatross, describing in detail the networking, all of the validator's functions and processes, the block's format, the misbehavior handling protocols, the rewards and punishme
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Albatross An optimistic consensus algorithm
259
nts, and the chain selection algorithm. 3 A. Networking We choose S/Kademlia [7] for peer routing. S/Kademlia is a hardened version of the Kademlia distributed hash table, which greatly improves resistance of the network to eclipse and Sybil attacks. We recommend that all communication between peers is encrypted and gossiped. By gossip we refer to when a node sends a message to its connected neighbors, those neighbors relay the message to their neighbors and so on until the message has been propagat
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Albatross An optimistic consensus algorithm
260
ed through the entire network. Always gossiping messages increases the DoS resistance of the validators. This is because each node only accepts incoming connections from a small set of other nodes and those connections tend to be long-lived. An attacker most likely won't be able to connect directly to a validator and must instead connect to other full nodes. Honest full nodes will not relay invalid messages and so end up acting as guards to the validators. As the number of honest full nodes increases, s
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Albatross An optimistic consensus algorithm
261
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Albatross An optimistic consensus algorithm
262
o does the resistance of the netwo
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Albatross An optimistic consensus algorithm
263
Blockchain and Consensus Algorithms in Internet of Things 978-1-5386-5925-0/18/$31.00 ©2018 IEEE Blockchain and Consensus Algorithms in Internet of Things Sorin Zoican Telecommunication Department Politehnica University Bucharest, Romania [email protected] Roxana Zoican Telecommunication Department Politehnica University Bucharest, Romania [email protected] Marius Vochin Telecommunication Department Politehnica University Bucharest, Romania [email protected] Dan G
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Blockchain and Consensus Algorithms in Internet of Things
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Blockchain and Consensus Algorithms in Internet of Things 978-1-5386-5925-0/18/$31.00 ©2018 IEEE Blockchain and Consensus Algorithms in Internet of Things Sorin Zoican Telecommunication Department Politehnica University Bucharest, Romania [email protected] Roxana Zoican Telecommunication Department Politehnica University Bucharest, Romania [email protected] Marius Vochin Telecommunication Department Politehnica University Bucharest, Romania [email protected] Dan G
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Blockchain and Consensus Algorithms in Internet of Things
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alatchi Telecommunication Department Politehnica University Bucharest, Romania [email protected] Abstract — this paper focuses on the performance evaluation of consensus algorithms used in a blockchain system for Internet of Things (IoT). In such systems the time necessary to achieve consensus should be small. Three most used consensus algorithms (modified proof of work, practical byzantine fault tolerance and binary consensus) are evaluated in different situations – type of motes, number
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Blockchain and Consensus Algorithms in Internet of Things
266
alatchi Telecommunication Department Politehnica University Bucharest, Romania [email protected] Abstract — this paper focuses on the performance evaluation of consensus algorithms used in a blockchain system for Internet of Things (IoT). In such systems the time necessary to achieve consensus should be small. Three most used consensus algorithms (modified proof of work, practical byzantine fault tolerance and binary consensus) are evaluated in different situations – type of motes, number
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Blockchain and Consensus Algorithms in Internet of Things
267
of nodes participating in consensus algorithm and radio propagation model. An integrated solution is proposed to adapt an IoT node to different consensus algorithm. The simulations in Contiki IoT operating system show good performance (time to achieve consensus less than seconds) Keywords— consensus algorithm, Internet of Things, blockchain I. INTRODUCTION The Internet of Things is nowadays in a continuous expansion [1]. Smart cities, intelligent houses and other applications require comm
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Blockchain and Consensus Algorithms in Internet of Things
268
of nodes participating in consensus algorithm and radio propagation model. An integrated solution is proposed to adapt an IoT node to different consensus algorithm. The simulations in Contiki IoT operating system show good performance (time to achieve consensus less than seconds) Keywords— consensus algorithm, Internet of Things, blockchain I. INTRODUCTION The Internet of Things is nowadays in a continuous expansion [1]. Smart cities, intelligent houses and other applications require comm
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Blockchain and Consensus Algorithms in Internet of Things
269
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Blockchain and Consensus Algorithms in Internet of Things
270
unication between a lot of nodes which usually consists of low or medium computational power and small memory amount microcontrollers. Generally, the IoT systems use a server-client communication model in which the devices are identified, authenticated and connected through servers with high computation and storage resources. The devices have a unique identity and they are connected through Internet. Nowadays this communication paradigm will not longer be used due the huge growing of the number of
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Blockchain and Consensus Algorithms in Internet of Things
271
IoT devices. The centralized solutions became expensive – they use many servers and networking equipment to ensure the communication between billions of devices and they need maintenance. Decentralized methods represent solutions that answer to the high costs issue in huge IoT systems. The computation power and storage requirements will be shared among the devices in the network. However, the peer to peer communication arises some important issues to solve: privacy, security, data validation and
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Blockchain and Consensus Algorithms in Internet of Things
272
IoT devices. The centralized solutions became expensive – they use many servers and networking equipment to ensure the communication between billions of devices and they need maintenance. Decentralized methods represent solutions that answer to the high costs issue in huge IoT systems. The computation power and storage requirements will be shared among the devices in the network. However, the peer to peer communication arises some important issues to solve: privacy, security, data validation and
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Blockchain and Consensus Algorithms in Internet of Things
273
consensus. These nodes must maintain a coherent data base with all information regard to the operations of cooperative nodes. An efficient solution to do this is blockchain technology [2]. It represents a distributed database with a continuous growing of the public data records (or blocks) added to it. The distributed database can be only extended, and previous inserted blocks can not be removed. The whole chain can not be replicated without very high costs. Each participant maintains a copy
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Blockchain and Consensus Algorithms in Internet of Things
274
consensus. These nodes must maintain a coherent data base with all information regard to the operations of cooperative nodes. An efficient solution to do this is blockchain technology [2]. It represents a distributed database with a continuous growing of the public data records (or blocks) added to it. The distributed database can be only extended, and previous inserted blocks can not be removed. The whole chain can not be replicated without very high costs. Each participant maintains a copy
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Blockchain and Consensus Algorithms in Internet of Things
275
of the blockchain and a new block will be inserted in the chain after consensus between participants is achieved. A centralized database (running over Internet) uses client-server network architecture. A client can change information on a centralized server (of course, if it has the permission to do this). Database control is maintained by a central authority. The main issue is the network security: if the central authority node is corrupt then all the nodes in the network will be at risk. In a
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Blockchain and Consensus Algorithms in Internet of Things
276
blockchain database, each node updates the information into the database working together to ensure the consensus providing built-in security for the network. In a blockchain system the nodes are connected (using different topologies – peer to peer, star) in a distributed system and each node contributes to decide using a consensus algorithm. Two main issues arise here: (a) the complexity of the consensus algorithm should be chosen taking into consideration the limited reso
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Blockchain and Consensus Algorithms in Internet of Things
277
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Blockchain and Consensus Algorithms in Internet of Things
278
Survey on Private Blockchain Consensus Algorithms Survey on Private Blockchain Consensus Algorithms Mr. Sunny Pahlajani Department of Computer Engineering, College of Engineering. Pune, India [email protected] Mr. Avinash Kshirsagar Department of Computer Engineering, College of Engineering. Pune, India [email protected] Dr. Vinod Pachghare Department of Computer Engineering, College of Engineering. Pune, India [email protected] Abstract— A blockchain
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Survey on Private Blockchain Consensus Algorithms
279
Survey on Private Blockchain Consensus Algorithms Survey on Private Blockchain Consensus Algorithms Mr. Sunny Pahlajani Department of Computer Engineering, College of Engineering. Pune, India [email protected] Mr. Avinash Kshirsagar Department of Computer Engineering, College of Engineering. Pune, India [email protected] Dr. Vinod Pachghare Department of Computer Engineering, College of Engineering. Pune, India [email protected] Abstract— A blockchain
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Survey on Private Blockchain Consensus Algorithms
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is a distributed ledger of records called as blocks. These blocks are linked using cryptographic hash. Each block contains a hash of the previous block, a timestamp, and transaction data. Consensus layer is the main layer in Blockchain Architecture, in which consensus protocol is configured to decide how new block is added in blockchain. Consensus algorithm solves the problem of trust in blockchain. Consensus algorithms can be classified into two classes. The first class is voting-based consensus
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Survey on Private Blockchain Consensus Algorithms
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, which requires nodes in the blockchain network to broadcast their results of mining a new block or transaction, before appending the block to blockchain. The second class is proof-based consensus, which requires the nodes joining the blockchain network to solve and mathematical puzzle to show that they are more eligible than the others to do the appending or mining work. Performance of blockchain can be increased with the use of suitable consensus algorithm. However, theory and data support for
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Survey on Private Blockchain Consensus Algorithms
282
, which requires nodes in the blockchain network to broadcast their results of mining a new block or transaction, before appending the block to blockchain. The second class is proof-based consensus, which requires the nodes joining the blockchain network to solve and mathematical puzzle to show that they are more eligible than the others to do the appending or mining work. Performance of blockchain can be increased with the use of suitable consensus algorithm. However, theory and data support for
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Survey on Private Blockchain Consensus Algorithms
283
the selecting suitable consensus in private blockchain is very limited. This paper contributes theory and data used for selecting suitable consensus algorithm and would help researchers for further exploring of consensus in private blockchain environment. Keywords—Proof-based consensus; Voting-based consensus; Byzantine fault tolerant consensus; Crash fault tolerant consensus. I. INTRODUCTION Blockchain is a distributed database existing on multiple nodes of the network at the same time
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Survey on Private Blockchain Consensus Algorithms
284
the selecting suitable consensus in private blockchain is very limited. This paper contributes theory and data used for selecting suitable consensus algorithm and would help researchers for further exploring of consensus in private blockchain environment. Keywords—Proof-based consensus; Voting-based consensus; Byzantine fault tolerant consensus; Crash fault tolerant consensus. I. INTRODUCTION Blockchain is a distributed database existing on multiple nodes of the network at the same time
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Survey on Private Blockchain Consensus Algorithms
285
in sync. It is a constantly growing ledger as new 'blocks', are added to it. Each block contains a timestamp and a link to the previous block, so they actually form a chain like structure tracking back to the root i,e. genesis block. No single node maintains the database, rather each node has a copy of database. Old blocks of transactions are preserved and new blocks are added to the ledger irreversibly, making it impossible to manipulate previously recorded transactions thus it leads to immutab
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Survey on Private Blockchain Consensus Algorithms
286
in sync. It is a constantly growing ledger as new 'blocks', are added to it. Each block contains a timestamp and a link to the previous block, so they actually form a chain like structure tracking back to the root i,e. genesis block. No single node maintains the database, rather each node has a copy of database. Old blocks of transactions are preserved and new blocks are added to the ledger irreversibly, making it impossible to manipulate previously recorded transactions thus it leads to immutab
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Survey on Private Blockchain Consensus Algorithms
287
le ledger. All blocks are encoded uniquely, so every node can verify the data however just a node who possesses a unique cryptographic key (private) can add another block to a specific chain. As long as you remain the only node who knows the key (private), nobody can control your exchanges. Likewise, cryptography is utilized to ensure synchronization of duplicates of the blockchain on every node in the network. You can consider blockchain as an advanced restorative record: each record is a bloc
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Survey on Private Blockchain Consensus Algorithms
288
le ledger. All blocks are encoded uniquely, so every node can verify the data however just a node who possesses a unique cryptographic key (private) can add another block to a specific chain. As long as you remain the only node who knows the key (private), nobody can control your exchanges. Likewise, cryptography is utilized to ensure synchronization of duplicates of the blockchain on every node in the network. You can consider blockchain as an advanced restorative record: each record is a bloc
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Survey on Private Blockchain Consensus Algorithms
289
k which has a mark expressing the date and time when the record was entered. The medicinal history is critical for conclusion and treatment purposes, so neither the specialist nor the patient ought to have the capacity to alter the records effectively made. In any case, the specialist claims a private key that enables him to make new records, and the patient possesses a public key that enables him to get to the records whenever required. This technique makes the information both open and secure.
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Survey on Private Blockchain Consensus Algorithms
290
k which has a mark expressing the date and time when the record was entered. The medicinal history is critical for conclusion and treatment purposes, so neither the specialist nor the patient ought to have the capacity to alter the records effectively made. In any case, the specialist claims a private key that enables him to make new records, and the patient possesses a public key that enables him to get to the records whenever required. This technique makes the information both open and secure.
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Survey on Private Blockchain Consensus Algorithms
291
In this way, blockchain is autonomous, straightforward, and secure. The upsides of such a distributed ledger are self- evident: being it cost and risk reduction, information security, or exchanges straightforwardness, organisations from most domains can clearly profit by this new innovation. The thought itself isn't new, however: it was initially illustrated in a 1976 research paper "New Directions in Cryptography" [1], yet for quite a while it was viewed as confused and not explored. Be that as
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Survey on Private Blockchain Consensus Algorithms
292
In this way, blockchain is autonomous, straightforward, and secure. The upsides of such a distributed ledger are self- evident: being it cost and risk reduction, information security, or exchanges straightforwardness, organisations from most domains can clearly profit by this new innovation. The thought itself isn't new, however: it was initially illustrated in a 1976 research paper "New Directions in Cryptography" [1], yet for quite a while it was viewed as confused and not explored. Be that as
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Survey on Private Blockchain Consensus Algorithms
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it may, in 2008 an obscure individual or group of individuals known by the pen name Nakamoto presented (Bitcoin) - a less complex usage of blockchain innovation as a digital currency [2]. Bitcoin ended up one of the main computerized monetary standards to utilize distributed innovation to encourage instant payments. On account of blockchain, it likewise turned into the principal computerized cash to tackle the issue of twofold spending. All the more essentially, Bitcoin is run by absolutely nobod
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Survey on Private Blockchain Consensus Algorithms
294
it may, in 2008 an obscure individual or group of individuals known by the pen name Nakamoto presented (Bitcoin) - a less complex usage of blockchain innovation as a digital currency [2]. Bitcoin ended up one of the main computerized monetary standards to utilize distributed innovation to encourage instant payments. On account of blockchain, it likewise turned into the principal computerized cash to tackle the issue of twofold spending. All the more essentially, Bitcoin is run by absolutely nobod
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Survey on Private Blockchain Consensus Algorithms
295
y and is immutable. The stability, security, and dispersed nature of Bitcoin made it one of the quickest developing resources: this year alone, its cost has ascended by over 500%. Thus, the developing notoriety of Bitcoin pulled in thoughtfulness regarding its fundamental innovation. Presently many new tech businesses are racing to deliver the Next Big Thing depending on blockchain, and an ever-increasing number of individuals working in finance and different areas start to perceive the down to
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Survey on Private Blockchain Consensus Algorithms
296
y and is immutable. The stability, security, and dispersed nature of Bitcoin made it one of the quickest developing resources: this year alone, its cost has ascended by over 500%. Thus, the developing notoriety of Bitcoin pulled in thoughtfulness regarding its fundamental innovation. Presently many new tech businesses are racing to deliver the Next Big Thing depending on blockchain, and an ever-increasing number of individuals working in finance and different areas start to perceive the down to
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Survey on Private Blockchain Consensus Algorithms
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practical benefits past the Bitcoin publicity. Over worldwide supply chains, financial administrations, medicinal services, governments and numerous different ventures, trailblazers are investigating approaches to utilize blockchain to upset and change conventional plans of action. Numerous industry chiefs have just accomplished noteworthy business benefits, including more prominent straightforwardness, upgraded security, enhanced detectability, expanded proficiency an
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Survey on Private Blockchain Consensus Algorithms
298
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Survey on Private Blockchain Consensus Algorithms
299