Pooling is not Favorable: Decentralize Mining Power of PoW Blockchain Using Age-of-Work

Shi, Long; Wang, Taotao; Li, Jun; Zhang, Shengli; Guo, Song

doi:10.1109/tcc.2022.3226496

Cited by 16 publications

(3 citation statements)

References 22 publications

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“…Certain modifications have been proposed for PoA to address these challenges. For instance, implementing a reputation-based system or penalties for misbehavior can mitigate the risk of collusion among validators 51 . Additionally, offering incentives in the form of transaction fees or token awards can promote active participation and ensure the stability and security of the network.…”

Section: Proof Of Authority (Poa)mentioning

confidence: 99%

Blockchain security enhancement: an approach towards hybrid consensus algorithms and machine learning techniques

Venkatesan,

Rahayu

2024

Sci Rep

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In this paper, we propose hybrid consensus algorithms that combine machine learning (ML) techniques to address the challenges and vulnerabilities in blockchain networks. Consensus Protocols make ensuring agreement among the applicants in the distributed systems difficult. However, existing mechanisms are more vulnerable to cyber-attacks. Previous studies extensively explore the influence of cyber attacks and highlight the necessity for effective preventive measures. This research presents the integration of ML techniques with the proposed hybrid consensus algorithms and advantages over predicting cyber-attacks, anomaly detection, and feature extraction. Our hybrid approaches leverage and optimize the proposed consensus protocols' security, trust, and robustness. However, this research also explores the various ML techniques with hybrid consensus algorithms, such as Delegated Proof of Stake Work (DPoSW), Proof of Stake and Work (PoSW), Proof of CASBFT (PoCASBFT), Delegated Byzantine Proof of Stake (DBPoS) for security enhancement and intelligent decision making in consensus protocols. Here, we also demonstrate the effectiveness of the proposed methodology within the decentralized networks using the ProximaX blockchain platform. This study shows that the proposed research framework is an energy-efficient mechanism that maintains security and adapts to dynamic conditions. It also integrates privacy-enhancing features, robust consensus mechanisms, and ML approaches to detect and prevent security threats. Furthermore, the practical implementation of these ML-based hybrid consensus models faces significant challenges, such as scalability, latency, throughput, resource requirements, and potential adversarial attacks. These challenges must be addressed to ensure the successful implementation of the blockchain network for real-world scenarios.

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Section: Proof Of Authority (Poa)mentioning

confidence: 99%

Blockchain security enhancement: an approach towards hybrid consensus algorithms and machine learning techniques

Venkatesan,

Rahayu

2024

Sci Rep

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“…After a transaction is processed by the network queue, each transaction routed by the network queue will leave the network queue and join the miner's mempool (consensus queue) after verification. Considering the exponential service distribution characteristic of PoW mining, as highlighted in previous studies [8,18,19], consensus queues are modeled as M/M/1/FCFS. This modeling approach takes into account the stochastic nature of mining and transaction processing within blockchain networks, where the service time for transactions (i.e., the time taken to mine a block and validate transactions) follows an exponential distribution.…”

Section: Model Assumptionmentioning

confidence: 99%

Solving Confirmation Time in Sharded Blockchain with PFQN

Wu,

Du,

Chen

et al. 2024

Electronics

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Sharding shows great potential for extending the efficiency of blockchains. The current challenge facing sharded blockchain technology lies in addressing the extended transaction confirmation times caused by isolated states between shards and unbalanced transaction allocation strategies. These factors contribute to an increase in cross-shard transactions and disproportionate shard workloads, ultimately resulting in indefinite confirmation delays for cross-shard transactions. A critical priority for sharded blockchain systems is to conduct a comprehensive qualitative analysis to better understand and mitigate the prolonged transaction confirmation times. We introduce a product-form queue network (PFQN) model to address the transaction confirmation time problem in sharded blockchains and incorporate a new confirmation queue to more accurately simulate the actual transaction confirmation process in the blockchain. In addition, we provide a detailed quantitative analysis of the relationship between the network load and consensus efficiency in sharded blockchains, offering a meaningful perspective for achieving robustness and efficiency in sharded blockchains. This research not only contributes to addressing the scalability issues in sharded blockchains but also offers a new perspective for future research directions.

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“…In contrast, blockchain, as a decentralized paradigm, offers a solution to mitigate attacks like single-point attacks. It operates similarly to entity-centric vehicle trust management, establishing a unified reputation system or making decisions based on neighboring user opinions [170]. By integrating FL and blockchain, some privacy concerns can be addressed, and issues related to untrusted data storage, centralized trust, and tampering in existing systems can be resolved [171].…”

Section: High Information Sensitivitymentioning

confidence: 99%

Enhanced Federated Learning for Edge Data Security in Intelligent Transportation Systems

Zhu

Yin

et al. 2023

IEEE Trans. Intell. Transport. Syst.

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Pooling is not Favorable: Decentralize Mining Power of PoW Blockchain Using Age-of-Work

Cited by 16 publications

References 22 publications

Blockchain security enhancement: an approach towards hybrid consensus algorithms and machine learning techniques

Blockchain security enhancement: an approach towards hybrid consensus algorithms and machine learning techniques

Solving Confirmation Time in Sharded Blockchain with PFQN

Enhanced Federated Learning for Edge Data Security in Intelligent Transportation Systems

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