Scalable Distributed Random Number Generation Based on Homomorphic Encryption

Nguyen-Van, Thanh; Nguyen-Anh, Tuan; Le, Tien-Dat; Nguyen-Ho, Minh-Phuoc; Nguyen-Van, Tuong; Le, Nhat-Quang; Nguyen-An, Khuong

doi:10.1109/blockchain.2019.00083

Cited by 17 publications

(21 citation statements)

References 7 publications

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“…PoSbased [88] CAbased [86] Underlying blockchain [58] Reference committee [31,59] VRF [89] Threshold signature [90] PVSS [58,59] Hash [31,91] VDF [92] Others [93,94] Binomial [58] Hypergeometric [59,95] Others [96] Strong consistency Weak consistency Partial sync.…”

Section: Powbasedmentioning

confidence: 99%

“…The homomorphic property of cryptosystems allows nodes to operate the ciphertext directly without decryption. Both HE-Rand 8 [93] and HERB [158] implement the threshold version of ElGamal as homomorphic encryption to generate randomness. Moreover, Zhang et al [94] define a threshold MA CP-ABE protocol and use it as a commit-and-reveal scheme to construct ABERand as a public distributed randomness beacon.…”

Section: Othersmentioning

confidence: 99%

“…In [126], RandHound and RandHerd are designed within a synchronous setting while RandShare is asynchronous. HE-Rand [93] is also synchronous as the protocol is described in rounds. RandRunner is designed for practical deployment scenarios with bounded network delay, while it still ensures liveness, public-verifiability, and bias-resistance even under periods of full asynchrony [153].…”

Section: Network Modelmentioning

confidence: 99%

“…As for computational and verification complexity, proof-of-work [1] and proof-of-delay [150] achieve high computational complexity for the reason that both of them rely on solving cryptographic puzzles. The VRF-based approaches such as Algorand [72], Ouroboros Praos [112], Caucus [151] (after the initial setup) as well as HE-Rand [93] are efficient, because they only require the verification of a VRF or hash preimage. The verification of RandRunner [153] only requires two hash functions and one verification algorithm with 2𝑡 as exponentiation (𝑇 = 2 𝑡 where 𝑇 is the time parameter of the VDF).…”

Section: Complexity Evaluationmentioning

confidence: 99%

“…Ouroboros [54], RandShare [126], Scrape [134] and HydRand [133] are more suitable for smaller groups due to their high communication complexity with the increasing number of nodes. Nguyen-Van et al [93] use homomorphic encryption (ElGamal on elliptic curves) to encrypt shares, while they do not consider a colluded user ("Requester"). Cachin et al [143] come with a formal security proof in the asynchronous network model, but it is based on elliptic curve pairings which are not yet well-established.…”

Section: Complexity Evaluationmentioning

confidence: 99%

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Building Blocks of Sharding Blockchain Systems: Concepts, Approaches, and Open Problems

Liu¹,

Liu²,

Salles³

et al. 2021

Preprint

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Sharding is the prevalent approach to breaking the trilemma of simultaneously achieving decentralization, security, and scalability in traditional blockchain systems, which are implemented as replicated state machines relying on atomic broadcast for consensus on an immutable chain of valid transactions. Sharding is to be understood broadly as techniques for dynamically partitioning nodes in a blockchain system into subsets (shards) that perform storage, communication, and computation tasks without fine-grained synchronization with each other. Despite much recent research on sharding blockchains, much remains to be explored in the design space of these systems. Towards that aim, we conduct a systematic analysis of existing sharding blockchain systems and derive a conceptual decomposition of their architecture into functional components and the underlying assumptions about system models and attackers they are built on. The functional components identified are node selection, epoch randomness, node assignment, intra-shard consensus, cross-shard transaction processing, shard reconfiguration, and motivation mechanism. We describe interfaces, functionality, and properties of each component and show how they compose into a sharding blockchain system. For each component, we systematically review existing approaches, identify potential and open problems, and propose future research directions. We focus on potential security attacks and performance problems, including system throughput and latency concerns such as confirmation delays. We believe our modular architectural decomposition and in-depth analysis of each component, based on a comprehensive literature study, provides a systematic basis for conceptualizing state-of-the-art sharding blockchain systems, proving or improving security and performance properties of components, and developing new sharding blockchain system designs.

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