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l Tree. This provides for efficient and secure verification of the transactions. As each block is connected to previous block by hash pointer it forms a hash chain which is unalterable. This makes blockchains inherently resistant to the tampering of the data. To maintain a distributed ledger, blockchain is managed by a peer to peer network which follows a protocol for validating new blocks. Each transaction in the public ledger is verified by consensus of a majority of the participants in the syst
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NoCo An Efficient Transaction Propagation Protocol for Open Blockchains
1,500
em. For the consensus it uses different consensus protocols like Proof of Stake (PoS) [3], Proof of Work (PoW) [1] and Proof of Burn (PoB). B. Blockchain Network A blockchain network comprises of several types of nodes which include full nodes, clients, propagating nodes, etc. The full nodes and propagating nodes maintain an updated state of the blockchain. 2018 Second International Conference on Advances in Computing, Control and Communication Technology (IAC3T) 978-1-5386-4146-0/18/$31.00 Β©2018
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NoCo An Efficient Transaction Propagation Protocol for Open Blockchains
1,501
em. For the consensus it uses different consensus protocols like Proof of Stake (PoS) [3], Proof of Work (PoW) [1] and Proof of Burn (PoB). B. Blockchain Network A blockchain network comprises of several types of nodes which include full nodes, clients, propagating nodes, etc. The full nodes and propagating nodes maintain an updated state of the blockchain. 2018 Second International Conference on Advances in Computing, Control and Communication Technology (IAC3T) 978-1-5386-4146-0/18/$31.00 Β©2018
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NoCo An Efficient Transaction Propagation Protocol for Open Blockchains
1,502
IEEE 41 When a new node joins the network it queries a number of DNS servers which provide a random set of (seed) nodes that are currently participating in the network [4]. Each node attempts to keep a minimum of 8 connections to other nodes open at all times. After joining, this new node queries it's peers and syncs the blockchain and pending transactions. C. Mining Mining is the process of adding a block to the blockchain by performing some mathematical computation on the block to satisfy t
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NoCo An Efficient Transaction Propagation Protocol for Open Blockchains
1,503
IEEE 41 When a new node joins the network it queries a number of DNS servers which provide a random set of (seed) nodes that are currently participating in the network [4]. Each node attempts to keep a minimum of 8 connections to other nodes open at all times. After joining, this new node queries it's peers and syncs the blockchain and pending transactions. C. Mining Mining is the process of adding a block to the blockchain by performing some mathematical computation on the block to satisfy t
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NoCo An Efficient Transaction Propagation Protocol for Open Blockchains
1,504
he required difficulty of the blockchain network. Those nodes who take part in mining process are miners. They need to invest a lot of power and computational resources to seal a new block using Proof of Work (PoW) computation. D. Block Consensus Protocol Since the blockchain is a ledger of transactions, the feature of prime importance would be consistency in the ledger across the network. Since the blockchain is a chain of blocks containing the details of transactions, the blockchain of each pee
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NoCo An Efficient Transaction Propagation Protocol for Open Blockchains
1,505
he required difficulty of the blockchain network. Those nodes who take part in mining process are miners. They need to invest a lot of power and computational resources to seal a new block using Proof of Work (PoW) computation. D. Block Consensus Protocol Since the blockchain is a ledger of transactions, the feature of prime importance would be consistency in the ledger across the network. Since the blockchain is a chain of blocks containing the details of transactions, the blockchain of each pee
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NoCo An Efficient Transaction Propagation Protocol for Open Blockchains
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r needs to be consistent. The consistency of the blockchain is maintained by the block consensus protocol. In this protocol, when a transaction arrives, miners add it to their transaction pool, from where they fetch a set of transactions to calculate a merkle hash of this set. Using this hash a Proof of Work solution is calculated (which should be less than the accepted difficulty of the network) and then a block is said to be mined. When a miner mines a block, it broadcasts the block to its peers
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NoCo An Efficient Transaction Propagation Protocol for Open Blockchains
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. The block received by the peer is validated by the peer and if the block passes the validation test, it is then broadcasted by that peer. Nodes add this bloc
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NoCo An Efficient Transaction Propagation Protocol for Open Blockchains
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A Survey on Security and Privacy Issues of Blockchain Technology 2019 International Conference on System Science and Engineering (ICSSE) 978-1-7281-0525-3/19/$31.00Β©2019 IEEE 362 A Survey on Security and Privacy Issues of Blockchain Technology Tam T. Huynh Faculty of Information Technology Posts and Telecommunications Institute of Technology Ho Chi Minh City, Vietnam [email protected] Thuc D. Nguyen Faculty of Information Technology University of Science, Ho Chi Minh City, V
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A Survey on Security and Privacy Issues of Blockchain Technology
1,509
A Survey on Security and Privacy Issues of Blockchain Technology 2019 International Conference on System Science and Engineering (ICSSE) 978-1-7281-0525-3/19/$31.00Β©2019 IEEE 362 A Survey on Security and Privacy Issues of Blockchain Technology Tam T. Huynh Faculty of Information Technology Posts and Telecommunications Institute of Technology Ho Chi Minh City, Vietnam [email protected] Thuc D. Nguyen Faculty of Information Technology University of Science, Ho Chi Minh City, V
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A Survey on Security and Privacy Issues of Blockchain Technology
1,510
ietnam [email protected] Hanh Tan Faculty of Information Technology Posts and Telecommunications Institute of Technology Ho Chi Minh City, Vietnam [email protected] Abstractβ€” Blockchain technology offers great benefits to the development of information technology. However, in order to use blockchain effectively, it is necessary to consider security and privacy aspects. This paper presents a survey of different security and privacy aspects of blockchain. In particular, we p
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A Survey on Security and Privacy Issues of Blockchain Technology
1,511
ietnam [email protected] Hanh Tan Faculty of Information Technology Posts and Telecommunications Institute of Technology Ho Chi Minh City, Vietnam [email protected] Abstractβ€” Blockchain technology offers great benefits to the development of information technology. However, in order to use blockchain effectively, it is necessary to consider security and privacy aspects. This paper presents a survey of different security and privacy aspects of blockchain. In particular, we p
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A Survey on Security and Privacy Issues of Blockchain Technology
1,512
resent the common types of security attacks on blockchain and security enhancement solutions. We also focus on the existing solutions to protect privacy for blockchain, and on the directions for future research using group signature and zero- knowledge schemes. Group signature scheme can be used to validate transactions in a blockchain network, and zero- knowledge to guarantee that transactions are valid despite the fact that the detailed information of transactions remains obscure. The combination
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A Survey on Security and Privacy Issues of Blockchain Technology
1,513
resent the common types of security attacks on blockchain and security enhancement solutions. We also focus on the existing solutions to protect privacy for blockchain, and on the directions for future research using group signature and zero- knowledge schemes. Group signature scheme can be used to validate transactions in a blockchain network, and zero- knowledge to guarantee that transactions are valid despite the fact that the detailed information of transactions remains obscure. The combination
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A Survey on Security and Privacy Issues of Blockchain Technology
1,514
of group signature and zero- knowledge could be feasible solutions for improving security and privacy for blockchain. This solution could also be deployed for IoT networks. Keywordsβ€”Blockchain, Security, Privacy, Group signature, Zero-knowledge. I. INTRODUCTION Blockchain is a technology in which blocks are linked together to form a chain as a linked list [1]. Each block has two main components, a block header and a block body [2]. The block header contains management information of block as
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A Survey on Security and Privacy Issues of Blockchain Technology
1,515
of group signature and zero- knowledge could be feasible solutions for improving security and privacy for blockchain. This solution could also be deployed for IoT networks. Keywordsβ€”Blockchain, Security, Privacy, Group signature, Zero-knowledge. I. INTRODUCTION Blockchain is a technology in which blocks are linked together to form a chain as a linked list [1]. Each block has two main components, a block header and a block body [2]. The block header contains management information of block as
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A Survey on Security and Privacy Issues of Blockchain Technology
1,516
well as chain. Meanwhile, the block body holds a list of transactions. Blockchain is a decentralized system, therefore the nodes communicate directly with each other through a peer-to-peer network and own a digital signature to validate their transactions. Additionally, some nodes have a ledger consisting of a sequence of blocks that they have reached consensus on [1]. In order to ensure the data on the ledger is synchronized, two consensus algorithms that are often used in blockchain technology a
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A Survey on Security and Privacy Issues of Blockchain Technology
1,517
well as chain. Meanwhile, the block body holds a list of transactions. Blockchain is a decentralized system, therefore the nodes communicate directly with each other through a peer-to-peer network and own a digital signature to validate their transactions. Additionally, some nodes have a ledger consisting of a sequence of blocks that they have reached consensus on [1]. In order to ensure the data on the ledger is synchronized, two consensus algorithms that are often used in blockchain technology a
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A Survey on Security and Privacy Issues of Blockchain Technology
1,518
re Proof of Work (PoW) and Proof of Stake (PoS) [1]. Blockchain technology has attracted significant attention from both researchers and government organizations because of the benefits that technology brings such as anonymity, transparency, decentralization, auditability [2, 3]. Blockchain could be applied in many different fields, including finance, medicine, transportation, agriculture, Internet of Things (IoT), etc [2, 4]. However, in order to use this technology effectively, we need to cons
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A Survey on Security and Privacy Issues of Blockchain Technology
1,519
re Proof of Work (PoW) and Proof of Stake (PoS) [1]. Blockchain technology has attracted significant attention from both researchers and government organizations because of the benefits that technology brings such as anonymity, transparency, decentralization, auditability [2, 3]. Blockchain could be applied in many different fields, including finance, medicine, transportation, agriculture, Internet of Things (IoT), etc [2, 4]. However, in order to use this technology effectively, we need to cons
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A Survey on Security and Privacy Issues of Blockchain Technology
1,520
ider challenges related to security and privacy. Most security attacks on blockchain originate from dishonest nodes, and aim to control the generation of blocks on the chain. In particular, a 50-percent attack [1, 3] can easily solve a hash puzzle in PoW to create a new block on the chain; in a double-spending attack [1, 3, 5], a dishonest node spends the same coin in the two transactions, and then extends the desired branch to form the longest valid branch of the chain; a selfish mining attac
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A Survey on Security and Privacy Issues of Blockchain Technology
1,521
ider challenges related to security and privacy. Most security attacks on blockchain originate from dishonest nodes, and aim to control the generation of blocks on the chain. In particular, a 50-percent attack [1, 3] can easily solve a hash puzzle in PoW to create a new block on the chain; in a double-spending attack [1, 3, 5], a dishonest node spends the same coin in the two transactions, and then extends the desired branch to form the longest valid branch of the chain; a selfish mining attac
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A Survey on Security and Privacy Issues of Blockchain Technology
1,522
k [1, 6] allows a dishonest node to publish their private blocks to the network to create a new longest valid chain; a dishonest node performs an eclipse attack [7] to isolate the victim's communications with other peers in the blockchain network, hence, can launch other types of attacks such as double-speding, selfish mining. Table I presents the common types of attacks on blockchain technology and defending solutions. TABLE I. TYPES OF ATTACKS AND DEFENDING SOLUTIONS Types of security attacks
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A Survey on Security and Privacy Issues of Blockchain Technology
1,523
k [1, 6] allows a dishonest node to publish their private blocks to the network to create a new longest valid chain; a dishonest node performs an eclipse attack [7] to isolate the victim's communications with other peers in the blockchain network, hence, can launch other types of attacks such as double-speding, selfish mining. Table I presents the common types of attacks on blockchain technology and defending solutions. TABLE I. TYPES OF ATTACKS AND DEFENDING SOLUTIONS Types of security attacks
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A Survey on Security and Privacy Issues of Blockchain Technology
1,524
Defending solutions 51 percent [1, 3, 12] Two-phase Proof of Work [21]. Random mining group selection technique [12]. Proof of Activity protocol [30]. Double spending [1, 3] PoW scheme and a distributed time- stamping service [10]. Waiting for more confirmations exponentially [14]. Listening Period, Inserting Observers and forwarding Double-spending Attempts [5]. Fair deposits [22]. Eclipse [7] Deterministic random eviction, Random selection, Test before evict, Feeler connections, Anchor
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A Survey on Security and Privacy Issues of Blockchain Technology
1,525
Defending solutions 51 percent [1, 3, 12] Two-phase Proof of Work [21]. Random mining group selection technique [12]. Proof of Activity protocol [30]. Double spending [1, 3] PoW scheme and a distributed time- stamping service [10]. Waiting for more confirmations exponentially [14]. Listening Period, Inserting Observers and forwarding Double-spending Attempts [5]. Fair deposits [22]. Eclipse [7] Deterministic random eviction, Random selection, Test before evict, Feeler connections, Anchor
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A Survey on Security and Privacy Issues of Blockchain Technology
1,526
connections, More buckets, More outgoing connections, Ban unsolicited ADDR messages, Diversify incoming connections and Anomaly detection [7]. Selfish mining [1,6] Freshness Preferred mechanism [26]. ZeroBlock scheme [27]. Decentralized backward-compatible defense mechanism [16]. Distributed denial of service [3, 17, 36] Proof of Activity protocol [30]. In blockchain technology, all transactions of nodes can be viewed and tracked. So, this technology cannot guarantee transactional pr
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A Survey on Security and Privacy Issues of Blockchain Technology
1,527
connections, More buckets, More outgoing connections, Ban unsolicited ADDR messages, Diversify incoming connections and Anomaly detection [7]. Selfish mining [1,6] Freshness Preferred mechanism [26]. ZeroBlock scheme [27]. Decentralized backward-compatible defense mechanism [16]. Distributed denial of service [3, 17, 36] Proof of Activity protocol [30]. In blockchain technology, all transactions of nodes can be viewed and tracked. So, this technology cannot guarantee transactional pr
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A Survey on Security and Privacy Issues of Blockchain Technology
1,528
ivacy [1, 2, 8, 9]. Some solutions have been proposed to protect privacy for blockhain technology such as: mixing technologies, zerocoin and zerocash [1, 34, 35]. Mixing technologies aim to confuse relationships between inputs and outputs of transactions. However, the content of transactions can still be viewed by the mixes. Meanwhile, zerocoin and zerocash solutions rely on cryptography algorithms to encrypt the content of transactions. In general, most of the proposed solutions cannot comprehe
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A Survey on Security and Privacy Issues of Blockchain Technology
1,529
ivacy [1, 2, 8, 9]. Some solutions have been proposed to protect privacy for blockhain technology such as: mixing technologies, zerocoin and zerocash [1, 34, 35]. Mixing technologies aim to confuse relationships between inputs and outputs of transactions. However, the content of transactions can still be viewed by the mixes. Meanwhile, zerocoin and zerocash solutions rely on cryptography algorithms to encrypt the content of transactions. In general, most of the proposed solutions cannot comprehe
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A Survey on Security and Privacy Issues of Blockchain Technology
1,530
nsively prevent security attacks from dishonest nodes. In addition, existing privacy-preserving solutions 2019 International Conference on System Science and Engineering (ICSSE) 363 based on cryptography are not suitable for IoT networks because the computing resources of IoT devices are limited. Hence, we propose a research direction to improve security and privacy-preserving for blockchain technology using group signature and zero-knowledge schemes. Our research direction ensures control
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A Survey on Security and Privacy Issues of Blockchain Technology
1,531
nsively prevent security attacks from dishonest nodes. In addition, existing privacy-preserving solutions 2019 International Conference on System Science and Engineering (ICSSE) 363 based on cryptography are not suitable for IoT networks because the computing resources of IoT devices are limited. Hence, we propose a research direction to improve security and privacy-preserving for blockchain technology using group signature and zero-knowledge schemes. Our research direction ensures control
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A Survey on Security and Privacy Issues of Blockchain Technology
1,532
of dishonest nodes in blockchain, and can be used to protect privacy for transactions in IoT networks. We summarize the contributions of this paper as follows: 1) We present a comprehensive survey on security attacks of blockchain technology. We describe in detail the common types of attacks and evaluate the security impacts on the blockchain network. 2) We review the existing researches to address security issues on blockchain. We also discuss the efficiencies and limitations of these solut
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A Survey on Security and Privacy Issues of Blockchain Technology
1,533
of dishonest nodes in blockchain, and can be used to protect privacy for transactions in IoT networks. We summarize the contributions of this paper as follows: 1) We present a comprehensive survey on security attacks of blockchain technology. We describe in detail the common types of attacks and evaluate the security impacts on the blockchain network. 2) We review the existing researches to address security issues on blockchain. We also discuss the efficiencies and limitations of these solut
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A Survey on Security and Privacy Issues of Blockchain Technology
1,534
ions. 3) To improve security and privacy aspects on blockchain, we suggest directions for future research using group signature and zero-knowledge schemes. Paper outline: The rest of the paper is organized as follows. In Section II, we present an overview of blockchain technology. Section III describes the common security attacks on blockchain and defending solutions. In Section IV, we discuss the existing solutions to enhance privacy aspect on blockchain. We describe our suggestive solution i
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A Survey on Security and Privacy Issues of Blockchain Technology
1,535
n Section V. The last section is conclusions. II. OVERVIEW OF BLOCKCHAIN TECHNOLOGY Blockchain was proposed in 2008 by an unknown author using the pseudonym Satoshi Nakamoto [10]. Blockchain uses cryptography, digital signature and consensus algorithms to ensure the security and data integrity in decentralized networks [1]. A blockchain can be viewed as a linked list of blocks, each block is linked to its predecessor via a hash pointer. A hash pointer contains a hash value of a block pointed
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A Survey on Security and Privacy Issues of Blockchain Technology
1,536
to at a fixed time. This hash value also helps verify the integrity of the content of the previous block [1]. Fig. 1. An example of blockchain. The first block of the chain is called genesis block which has no parent block [1, 2]. A. Block Structure Each block consists of two main components that are the block header and the block body as shown in Fig. 1. The major fields of the block header are shown in Table II below. TABLE II. THE MAIN
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A Survey on Security and Privacy Issues of Blockchain Technology
1,537
to at a fixed time. This hash value also helps verify the integrity of the content of the previous block [1]. Fig. 1. An example of blockchain. The first block of the chain is called genesis block which has no parent block [1, 2]. A. Block Structure Each block consists of two main components that are the block header and the block body as shown in Fig. 1. The major fields of the block header are shown in Table II below. TABLE II. THE MAIN
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A Survey on Security and Privacy Issues of Blockchain Technology
1,538
The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work Moritz Platt1, Johannes Sedlmeir2, Daniel Platt3, Jiahua Xu4, Paolo Tasca4, Nikhil Vadgama4, and Juan Ignacio IbaΓ±ez4 1Department of Informatics, King's College London, London, UK 2FIM Research Center, University of Bayreuth, Bayreuth, Germany 3Department of Mathematics, Imperial College London, London, UK 4Centre for Blockchain Technologies, Univer
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The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work
1,539
The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work Moritz Platt1, Johannes Sedlmeir2, Daniel Platt3, Jiahua Xu4, Paolo Tasca4, Nikhil Vadgama4, and Juan Ignacio IbaΓ±ez4 1Department of Informatics, King's College London, London, UK 2FIM Research Center, University of Bayreuth, Bayreuth, Germany 3Department of Mathematics, Imperial College London, London, UK 4Centre for Blockchain Technologies, Univer
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The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work
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sity College London, London, UK [email protected], [email protected], [email protected], {jiahua.xu, p.tasca, nikhil.vadgama, j.ibanez}@ucl.ac.uk Abstractβ€”Popular permissionless distributed ledger technology (DLT) systems using proof-of-work (PoW) for Sybil attack resist- ance have extreme energy requirements, drawing stern criticism from academia, business and the media. DLT systems building on alternative consensus mechanisms, particularly proof-of-stake (PoS), aim to address th
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The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work
1,541
sity College London, London, UK [email protected], [email protected], [email protected], {jiahua.xu, p.tasca, nikhil.vadgama, j.ibanez}@ucl.ac.uk Abstractβ€”Popular permissionless distributed ledger technology (DLT) systems using proof-of-work (PoW) for Sybil attack resist- ance have extreme energy requirements, drawing stern criticism from academia, business and the media. DLT systems building on alternative consensus mechanisms, particularly proof-of-stake (PoS), aim to address th
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The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work
1,542
is downside. In this paper, we take an initial step towards comparing the energy requirements of such systems to understand whether they achieve this goal equally well. While multiple studies have analysed the energy demands of individual blockchains, little comparative work has been done. We approach this research gap by formalising a basic consumption model for PoS blockchains. Applying this model to six archetypal blockchains generates three main findings. First, we confirm the concerns around the ener
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The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work
1,543
is downside. In this paper, we take an initial step towards comparing the energy requirements of such systems to understand whether they achieve this goal equally well. While multiple studies have analysed the energy demands of individual blockchains, little comparative work has been done. We approach this research gap by formalising a basic consumption model for PoS blockchains. Applying this model to six archetypal blockchains generates three main findings. First, we confirm the concerns around the ener
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The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work
1,544
gy footprint of PoW by showing that Bitcoin's energy consumption exceeds the energy consumption of all PoS- based systems analysed by at least three orders of magnitude. Second, we illustrate that there are significant differences in energy consumption among the PoS-based systems analysed, with permis- sionless systems having a larger energy footprint overall owing to their higher replication factor. Third, we point out that the type of hardware that validators use has a considerable impact on whether the
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The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work
1,545
gy footprint of PoW by showing that Bitcoin's energy consumption exceeds the energy consumption of all PoS- based systems analysed by at least three orders of magnitude. Second, we illustrate that there are significant differences in energy consumption among the PoS-based systems analysed, with permis- sionless systems having a larger energy footprint overall owing to their higher replication factor. Third, we point out that the type of hardware that validators use has a considerable impact on whether the
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The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work
1,546
energy consumption of PoS blockchains is comparable with or considerably larger than that of centralised systems. Index Termsβ€”Blockchain, Carbon Footprint, Distributed Ledger Technology, Proof-of-Stake, Sustainability, Climate Action I. Introduction In decentralised distributed ledger technology (DLT) systems, consensus mechanisms fulfil multiple purposes surrounding the proposal, validation, propagation and finalisation of data [1]. Voting is used extensively in common consensus mechanisms to resolve
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The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work
1,547
energy consumption of PoS blockchains is comparable with or considerably larger than that of centralised systems. Index Termsβ€”Blockchain, Carbon Footprint, Distributed Ledger Technology, Proof-of-Stake, Sustainability, Climate Action I. Introduction In decentralised distributed ledger technology (DLT) systems, consensus mechanisms fulfil multiple purposes surrounding the proposal, validation, propagation and finalisation of data [1]. Voting is used extensively in common consensus mechanisms to resolve
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The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work
1,548
ambiguity arising from actors that spread incorrect or conflicting information [2]. Sybil attacks, which pose a critical problem for DLT systems, occur when an attacker creates an artificially large number of bogus identities [3] to skew the results of majority decisions on the admission and order of transactions. In permissioned networks, gatekeeping strategies can be applied that limit access to a network to previously vetted actors [4], thereby preventing such attacks. However, for permissionless netw
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The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work
1,549
ambiguity arising from actors that spread incorrect or conflicting information [2]. Sybil attacks, which pose a critical problem for DLT systems, occur when an attacker creates an artificially large number of bogus identities [3] to skew the results of majority decisions on the admission and order of transactions. In permissioned networks, gatekeeping strategies can be applied that limit access to a network to previously vetted actors [4], thereby preventing such attacks. However, for permissionless netw
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The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work
1,550
orks, in which participants can partake in consensus without any control [5], more complex mechanisms need to be applied to combat Sybil attacks. These commonly entail aligning entitlement to participate in consensus proportionally with the possession or expenditure of resources that can be digitally verified [1]. Proof-of-work (PoW) is an example of a Sybil attack resistance scheme that has been used in most early cryptocurrencies such as Bitcoin [6]. To counteract Sybil attacks, PoW uses cryptographic
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The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work
1,551
orks, in which participants can partake in consensus without any control [5], more complex mechanisms need to be applied to combat Sybil attacks. These commonly entail aligning entitlement to participate in consensus proportionally with the possession or expenditure of resources that can be digitally verified [1]. Proof-of-work (PoW) is an example of a Sybil attack resistance scheme that has been used in most early cryptocurrencies such as Bitcoin [6]. To counteract Sybil attacks, PoW uses cryptographic
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The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work
1,552
puzzles of configurable difficulty with efficient verification so that it becomes computationally expensive for attackers to interfere with consensus [7]. However, the energy consumption of PoW- based cryptocurrencies is connected to their respective market capitalisations, leading to extreme energy demand for popular implementations [8]. For instance, the electricity demand of Bitcoin is now in the same range as that of entire industrialised nations [9] and has been positioned as a dangerous contributor
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The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work
1,553
puzzles of configurable difficulty with efficient verification so that it becomes computationally expensive for attackers to interfere with consensus [7]. However, the energy consumption of PoW- based cryptocurrencies is connected to their respective market capitalisations, leading to extreme energy demand for popular implementations [8]. For instance, the electricity demand of Bitcoin is now in the same range as that of entire industrialised nations [9] and has been positioned as a dangerous contributor
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The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work
1,554
to global warming, producing up to 22.90Mt CO2 [10]. Against this backdrop, many alternatives to PoW have been proposed that do not rely on extensive computational effort [11]. Among these is proof-of-stake (PoS), in which participants with larger holdings of a cryptocurrency have a greater influence in trans- action validation. While PoS is generally understood as being more energy-efficient than PoW, the exact energy consumption characteristics of PoS-based systems, and the influence that network throu
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The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work
1,555
to global warming, producing up to 22.90Mt CO2 [10]. Against this backdrop, many alternatives to PoW have been proposed that do not rely on extensive computational effort [11]. Among these is proof-of-stake (PoS), in which participants with larger holdings of a cryptocurrency have a greater influence in trans- action validation. While PoS is generally understood as being more energy-efficient than PoW, the exact energy consumption characteristics of PoS-based systems, and the influence that network throu
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The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work
1,556
ghput has on them, are not widely understood. Two main approaches to quantifying the energy consumption of a DLT system have been used in the past. One is to measure the consumption of a representative participant node and then extrapolate from this measurement. An alternative approach is to develop a mathematical model that includes the core metrics of a DLT system to calculate its energy consumption. Extensive research efforts have cumulated in best practices for determining the energy consumption of D
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The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work
1,557
ghput has on them, are not widely understood. Two main approaches to quantifying the energy consumption of a DLT system have been used in the past. One is to measure the consumption of a representative participant node and then extrapolate from this measurement. An alternative approach is to develop a mathematical model that includes the core metrics of a DLT system to calculate its energy consumption. Extensive research efforts have cumulated in best practices for determining the energy consumption of D
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The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work
1,558
LT systems [12]. So far, most work has focused on PoW blockchains1, and some research has investigated individual non-PoW systems. In this paper we propose a simple energy consumption model, applicable to a broad range of DLT systems that use PoS for Sybil attack resistance. Specifically, this model considers the number of validator nodes, their energy consumption, and the network throughput, based on which the energy consumption per transaction is estimated. We present the results of applying 1For the p
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The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work
1,559
LT systems [12]. So far, most work has focused on PoW blockchains1, and some research has investigated individual non-PoW systems. In this paper we propose a simple energy consumption model, applicable to a broad range of DLT systems that use PoS for Sybil attack resistance. Specifically, this model considers the number of validator nodes, their energy consumption, and the network throughput, based on which the energy consumption per transaction is estimated. We present the results of applying 1For the p
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The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work
1,560
urpose of this manuscript, the term 'Blockchain' refers to any type of DLT, even if it does not make use of the 'block' concept, first described by Nakamoto [6]. 1135 2021 IEEE 21st International Conference on Software Quality, Reliability and Security Companion (QRS-C) 2693-9371/21/$31.00 Β©2021 IEEE DOI 10.1109/QRS-C55045.2021.00168 20 21 IE EE 2 1s t I nt er na tio na l C on fe re nc e on S of tw ar e Q ua lit y, R el ia bi lit y an d Se cu rit y Co m pa ni on (Q RS
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The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work
1,561
urpose of this manuscript, the term 'Blockchain' refers to any type of DLT, even if it does not make use of the 'block' concept, first described by Nakamoto [6]. 1135 2021 IEEE 21st International Conference on Software Quality, Reliability and Security Companion (QRS-C) 2693-9371/21/$31.00 Β©2021 IEEE DOI 10.1109/QRS-C55045.2021.00168 20 21 IE EE 2 1s t I nt er na tio na l C on fe re nc e on S of tw ar e Q ua lit y, R el ia bi lit y an d Se cu rit y Co m pa ni on (Q RS
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The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work
1,562
-C ) | 9 78 -1 -6 65 4- 78 36 -6 /2 1/ $3 1. 00 Β© 20 21 IE EE | D O I: 10 .1 10 9/ Q RS -C 55 04 5. 20 21 .0 01 68 Authorized licensed use limited to: University College London. Downloaded on July 04,2023 at 16:25:58 UTC from IEEE Xplore. Restrictions apply. this model to six PoS-based systems. Our results suggest that, while negligible compared to PoW, the energy consumption of PoS systems can still vary significantly. The next section reviews related work in both experime
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The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work
1,563
-C ) | 9 78 -1 -6 65 4- 78 36 -6 /2 1/ $3 1. 00 Β© 20 21 IE EE | D O I: 10 .1 10 9/ Q RS -C 55 04 5. 20 21 .0 01 68 Authorized licensed use limited to: University College London. Downloaded on July 04,2023 at 16:25:58 UTC from IEEE Xplore. Restrictions apply. this model to six PoS-based systems. Our results suggest that, while negligible compared to PoW, the energy consumption of PoS systems can still vary significantly. The next section reviews related work in both experime
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The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work
1,564
ntal and mathematical models. We then briefly describe the relevant architectural features of selected PoS systems. In the following section, we introduce our model in detail and describe how the underlying data were obtained. Subsequently, we apply the model to the systems selected, present the comparative results, and discuss the limitations. Finally, we conclude our study with potential avenues for future research. II. Related work We conducted an informal literature review2 using the 'Bielefeld Aca
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The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work
1,565
ntal and mathematical models. We then briefly describe the relevant architectural features of selected PoS systems. In the following section, we introduce our model in detail and describe how the underlying data were obtained. Subsequently, we apply the model to the systems selected, present the comparative results, and discuss the limitations. Finally, we conclude our study with potential avenues for future research. II. Related work We conducted an informal literature review2 using the 'Bielefeld Aca
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The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work
1,566
demic Search Engine', a popular academic search system meeting all the necessary quality requirements for a systematic literature review [13]. We thereby obtained 413 results of prior studies analysing the energy demand of different DLT systems, with a significant focus on PoW blockchains in general, and specifically on Bitcoin Commonly, models take one of the following two forms. Experimental models: The first form revolves around conducting experiments using mining hardware and measuring its actual ene
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The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work
1,567
demic Search Engine', a popular academic search system meeting all the necessary quality requirements for a systematic literature review [13]. We thereby obtained 413 results of prior studies analysing the energy demand of different DLT systems, with a significant focus on PoW blockchains in general, and specifically on Bitcoin Commonly, models take one of the following two forms. Experimental models: The first form revolves around conducting experiments using mining hardware and measuring its actual ene
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The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work
1,568
rgy consumption, as performed by Igumenov et al. with different configurations of computational resources [14]. This approach has been used to derive consumption characteristics for different usage scenarios. The 'BCTMark' framework [15], for instance, allows for the deployment of an entire experiment stack, including the DLT system under test. Using load generators, a realistic network workload can be created. The effects on the energy consumption of this setup under varying loads can subsequently be mea
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The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work
1,569
rgy consumption, as performed by Igumenov et al. with different configurations of computational resources [14]. This approach has been used to derive consumption characteristics for different usage scenarios. The 'BCTMark' framework [15], for instance, allows for the deployment of an entire experiment stack, including the DLT system under test. Using load generators, a realistic network workload can be created. The effects on the energy consumption of this setup under varying loads can subsequently be mea
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The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work
1,570
sured via energy sensors connected to the testbed. An experimental study on the energy consumption of the permissioned, non-PoW XRP ledger demonstrates that customising validator hardware can yield reductions in energy demand [16]. Metrics reported for common cryptocurrencies have been combined with testbed experiments to model the energy consumption behaviours of various consensus algorithms [17]. Mathematical models: An alternative method is to quantify assumptions about the environment in which a DLT
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The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work
1,571
sured via energy sensors connected to the testbed. An experimental study on the energy consumption of the permissioned, non-PoW XRP ledger demonstrates that customising validator hardware can yield reductions in energy demand [16]. Metrics reported for common cryptocurrencies have been combined with testbed experiments to model the energy consumption behaviours of various consensus algorithms [17]. Mathematical models: An alternative method is to quantify assumptions about the environment in which a DLT
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The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work
1,572
system operates. Often, such models use a 'top-down' approach that relies on publicly observable factors – such as the hash rate in the case of Bitcoin – and associates them with common mining hardware or even seeks to determine the hardware used via surveys [12]. The papers of GallersdΓΆrfer et al. [18], KΓΌfeo- glu and Γ–zkuran [19], and Zade et al. [20] are examples of this hash rate-based approach. Sedlmeir et al. [8] undertake a basic comparison of different DLT architectures with the conclusion that th
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The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work
1,573
system operates. Often, such models use a 'top-down' approach that relies on publicly observable factors – such as the hash rate in the case of Bitcoin – and associates them with common mining hardware or even seeks to determine the hardware used via surveys [12]. The papers of GallersdΓΆrfer et al. [18], KΓΌfeo- glu and Γ–zkuran [19], and Zade et al. [20] are examples of this hash rate-based approach. Sedlmeir et al. [8] undertake a basic comparison of different DLT architectures with the conclusion that th
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The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work
1,574
e energy consumption differs significantly depending on the design chosen. A further study by the same authors [21] refines previous models for measuring the power consumption 2This was done using the query ("Blockchain" OR "DLT" OR "Distributed Ledger") AND ("Energy Consumption" OR "Energy Demand" OR "Electricity Demand" OR "Carbon Footprint") year:[2008 TO *]. of Bitcoin, such as the one by Vranken [22], and emphasises that the driving forces behind power consumption are the Bitcoin price and the avai
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The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work
1,575
lability of cheap electricity. Eshani et al. [23] use a linear regression model to predict Ethereum's energy con- sumption based on the observed hash rate and difficulty level; however, the use of simplistic interpolation techniques alone is likely not an appropriate method for PoW blockchains [12]. Powell et al. [24] derive a mathematical model for the energy consumption of the PoS-based Polkadot blockchain by extra- polating from the power demand of a single validator machine. III. Systems reviewed Th
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The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work
1,576
is paper compares six DLT systems, both permissioned and permissionless, with high market capitalisation that use PoS as part of the consensus mechanism. To reiterate: PoS systems are conceptualised in such a way that the eligibility to actively participate in their consensus mechanism is proportional to the amount of cryptocurrency a participant holds. This means that the resource 'computing power', as used in PoW, is replaced by the resource 'capital' [8]. While the systems compared use dif- ferent PoS-
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The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work
1,577
based consensus mechanisms that have different par- ticipation requirements, such as a minimum balance or a com- mitment to staking capital for a pre-defined period, they share important commonalities. A commonality particularly relevant to energy consumption is the need for dedicated servers, valid- ator nodes, to validate sets of transactions and attach generation proofs. This activity is essential, irrespective of whether transac- tions are organised as chains of blocks [1], or as directed acyclic grap
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The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work
1,578
hs [25]. It is this validation and proof generation aspect that attracts stern criticism in the context of PoW since it is respons- ible for its problematic energy consumption characteristics [1]. Platform Permissioned Permissionless Ethereum 2.0 β€’ Algorand β€’ Cardano β€’ Polkadot β€’ Tezos β€’ Hedera β€’ Table I Comparison of the analysed DLT systems in node permission setting. The selection process for validation and proof generation in PoS constitutes a pseudo-random procedure in which a higher stake yields
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The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work
1,579
a higher probability of being selected [26]. PoS can be applied in both permissioned [27] and permissionless [28] settings (see Table I). Participants in permissionless networks can contribute validator nodes by following the respective admission procedures, such as broadcasting a key registration transaction in the case of Algorand [29]. The procedures often involve staking cryptocurrency and emitting messages on the ledger to indicate the willingness to act as validator [30]. In permissioned systems, su
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The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work
1,580
a higher probability of being selected [26]. PoS can be applied in both permissioned [27] and permissionless [28] settings (see Table I). Participants in permissionless networks can contribute validator nodes by following the respective admission procedures, such as broadcasting a key registration transaction in the case of Algorand [29]. The procedures often involve staking cryptocurrency and emitting messages on the ledger to indicate the willingness to act as validator [30]. In permissioned systems, su
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The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work
1,581
ch as Hedera, participation in the pseudo-random selection procedure is, however, limited to participants previously determined via an off-ledger process [31]. Once a node is recognised as a validator, it 1136 Authorized licensed use limited to: University College London. Downloaded on July 04,2023 at 16:25:58 UTC from IEEE Xplore. Restrictions apply. may participate in validation and proof generation. Depending on the particulars of the consensus mechanism, selection may require additional protoco
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The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work
1,582
ch as Hedera, participation in the pseudo-random selection procedure is, however, limited to participants previously determined via an off-ledger process [31]. Once a node is recognised as a validator, it 1136 Authorized licensed use limited to: University College London. Downloaded on July 04,2023 at 16:25:58 UTC from IEEE Xplore. Restrictions apply. may participate in validation and proof generation. Depending on the particulars of the consensus mechanism, selection may require additional protoco
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The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work
1,583
l steps, such as election onto a committee [29]. Once selected, validator nodes will verify the transactions received and generate proofs of validation, most commonly in the form of cryptographic signatures. In summary, the commonalities of the protocols analysed can be described as follows: in all protocols, participants can act as validators, thereby qualifying to perform transaction validation and proof generation. In permissioned networks, the set of participants that can act as validators is limited
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The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work
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. In permissionless networks, there are no such limitatio
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The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work
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<concept><concept_id>10002950.10003714.10003739</concept_id><concept_desc>Mathematics of computing~Nonlinear equations</concept_desc><concept_significance>500</concept_significance></concept> Development of a Distributed Blockchain eVoting System Ishaku Liti Awalu Computer Science Department Sangmyung University Seoul South Korea +82 102 8624557 [email protected] Park Hung Kook Computer Science Department Sangmyung University Seoul South Korea +82 109 1541509 [email protected] Joa Sa
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Development of a Distributed Blockchain eVoting System
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<concept><concept_id>10002950.10003714.10003739</concept_id><concept_desc>Mathematics of computing~Nonlinear equations</concept_desc><concept_significance>500</concept_significance></concept> Development of a Distributed Blockchain eVoting System Ishaku Liti Awalu Computer Science Department Sangmyung University Seoul South Korea +82 102 8624557 [email protected] Park Hung Kook Computer Science Department Sangmyung University Seoul South Korea +82 109 1541509 [email protected] Joa Sa
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Development of a Distributed Blockchain eVoting System
1,587
n Lim Computer Science Department Sangmyung University Seoul South Korea +82 103 2342035 [email protected] ABSTRACT Over the years, elections at different levels are the subject of many disputes, consolidation and reaffirmation of confidence in different leaders. These elections range from either boardroom elections, local elections to national elections. Correspondingly, electioneering as an institutional process has transformed with both technological advancements as well politica
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Development of a Distributed Blockchain eVoting System
1,588
n Lim Computer Science Department Sangmyung University Seoul South Korea +82 103 2342035 [email protected] ABSTRACT Over the years, elections at different levels are the subject of many disputes, consolidation and reaffirmation of confidence in different leaders. These elections range from either boardroom elections, local elections to national elections. Correspondingly, electioneering as an institutional process has transformed with both technological advancements as well politica
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Development of a Distributed Blockchain eVoting System
1,589
l sophistication. Blockchain as a nascent technology has ushered in a range of opportunities in different sectors such as finance, real estate, supply chain management, medical records, elections etc. In this paper, we leveraged on some of the key characteristics of Blockchain technology in form of immutability, auditability, confidentiality, transparency, decentralization etc to develop a Blockchain eVoting network system that can be utilized for geographically dispersed elections. Key us
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Development of a Distributed Blockchain eVoting System
1,590
ers of the system or actors were isolated and their interactions with the system identified using Use Case Methodology. The system actors are the voters, miners that consists of Universities and public libraries, central authority, candidates and the voters. The different stages of an election process such as pre-election, registration of both candidates and voters, voting/balloting, tallying and auditing were equally enumerated. The interactions of the actors with the system were equally
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Development of a Distributed Blockchain eVoting System
1,591
ers of the system or actors were isolated and their interactions with the system identified using Use Case Methodology. The system actors are the voters, miners that consists of Universities and public libraries, central authority, candidates and the voters. The different stages of an election process such as pre-election, registration of both candidates and voters, voting/balloting, tallying and auditing were equally enumerated. The interactions of the actors with the system were equally
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Development of a Distributed Blockchain eVoting System
1,592
captured, analyzed and used to develop the conceptual system. The proposed system is made up of a multichain Blockchain network, an arbitration server, distributed database, an interactive, multi-device graphic user interface GUI, and an application server. To engender anonymity, a combination of Digital Signature and Secure Hash Algorithm SHA was proposed, also Proof of Work PoW was the proposed consensus algorithm. The identified stages of the election were evaluated against the requirem
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Development of a Distributed Blockchain eVoting System
1,593
ents of an eVoting system. The proposed system was found to satisfy the requirements of an eVoting system such as transparency, privacy, scalability, receipt freeness, security, integrity, accuracy, auditable etc. CCS Concepts β€’ General and reference➝Cross-computing tools and techniques➝Design Keywords Blockchain, eVoting, Multichain, Elections. 1. INTRODUCTION Modes and methods of monitoring citizens' opinions and decisions are often conveyed in form of elections or referendums condu
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Development of a Distributed Blockchain eVoting System
1,594
ents of an eVoting system. The proposed system was found to satisfy the requirements of an eVoting system such as transparency, privacy, scalability, receipt freeness, security, integrity, accuracy, auditable etc. CCS Concepts β€’ General and reference➝Cross-computing tools and techniques➝Design Keywords Blockchain, eVoting, Multichain, Elections. 1. INTRODUCTION Modes and methods of monitoring citizens' opinions and decisions are often conveyed in form of elections or referendums condu
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Development of a Distributed Blockchain eVoting System
1,595
cted through democratically accepted voting processes. Groups of individuals (which range from a small group up to national sizes) employ voting as a method to indicate the group's formal decision-making process either to select an individual into a leadership position or to accept or reject a political position or proposition. In other circumstances, it is used as a process of reinforcing or affirming a leadership or proposition. The history of contemporary formal elections can be traced as
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Development of a Distributed Blockchain eVoting System
1,596
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Development of a Distributed Blockchain eVoting System
1,597
far back as the 17th century [1]. Its emergence is mainly attributed to the adoption of representative government systems in the western countries and its corresponding evolution has witness significant transformations in terms` 244 of the processes and methods, legislations, technology etc. These transformations are often geared towards engendering inclusiveness and acceptability by stimulating trust in the public. This is often translated in form of reform acts to increase certain socia
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Development of a Distributed Blockchain eVoting System
1,598
far back as the 17th century [1]. Its emergence is mainly attributed to the adoption of representative government systems in the western countries and its corresponding evolution has witness significant transformations in terms` 244 of the processes and methods, legislations, technology etc. These transformations are often geared towards engendering inclusiveness and acceptability by stimulating trust in the public. This is often translated in form of reform acts to increase certain socia
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Development of a Distributed Blockchain eVoting System
1,599