The Evolution of Mining Pools and Miners’ Behaviors in the Bitcoin Blockchain

Tovanich, Natkamon; Soulié, Nicolas; Isenberg, Petra

doi:10.1109/tnsm.2022.3159004

Cited by 14 publications

(8 citation statements)

References 23 publications

(33 reference statements)

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“…ξ H ≤ ξ C ), we present in Fig- ure 4 a historical data 5 for p, q and the accompanying values of q/p. More in-depth analysis regarding mining pools are provided in [51]. It can be noticed from the figure that inequality 18 holds indeed since the year 2010 (thus associated with the emergence of mining pools), while the maximum portion, historically ever, controlled by a single mining pool, was reached in the year 2013.…”

Section: Partial Preimage Attackmentioning

confidence: 97%

Bitcoin Revisited: Formalization, Benchmarking, and Open Security Issues

Baniata¹,

Kertész²

2022

Preprint

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<p>Thousands of researchers and practitioners around the world neglect foundational understanding of the most trusted cryptocurrency platform, Bitcoin. According to the typical tendency of taking the discussion of Bitcoin's security for granted, it is usually confidently stated that, technically, Bitcoin is one of the most secure platforms for investment. In this paper, we revisit the fundamental calculations and assumptions of this widely adopted platform. We break down the original calculations in order to better understand the underlying assumptions of the Bitcoin proposal. Accordingly, we set open research questions, and we highlight expected scenarios upon the violation of each assumption. Furthermore, we propose a novel formalization of the Bitcoin mining problem using the Birthday Paradox, which we utilize to propose new concepts for benchmarking the security of Bitcoin, including the Critical Difficulty and Critical Difficulty per given portion. Our calculations indicated that it would be profitable to launch Partial Pre-Image attacks on Bitcoin once the mining puzzle difficulty reaches 56 leading zeros. Additionally, we discuss how Quantum Computing can be used to attack Bitcoin, and the implications of Sharding on the security of Bitcoin. The main objective of this work is to highlight, demystify, and justify the confusion between the realistic relative trust versus the common unconditional trust in Bitcoin.</p>

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Section: Partial Preimage Attackmentioning

confidence: 97%

Bitcoin Revisited: Formalization, Benchmarking, and Open Security Issues

Baniata¹,

Kertész²

2022

Preprint

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“…Bitcoin functions through a decentralized peer-to-peer (P2P) network, where transactions are documented on a public ledger known as the blockchain [43]- [45]. However, to prevent double spending, these transactions need to be propagated and confirmed by the network [46]- [48]. Key mechanisms to prevent double spending are as follows: i) Blockchain confirmation: miners verify the validity of transactions before adding them to a block.…”

Section: Double Spendingmentioning

confidence: 99%

Improved DAG in blockchain tangle for IOTA

Rhee,

Lee

2024

IJEECS

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The internet of things (IoT) enables machine-to-machine communication without human intervention. Consequently, every object connected to the internet can exchange information with each other. Internet of things application (IOTA) has undertaken a project to address the high transaction fees inherent in traditional blockchain systems and enhance the efficiency of microtransactions between machines by combining blockchain and IoT. IOTA employs its unique Tangle technology, which introduces a novel transaction consensus method, addressing the fee issues, limited scalability, and the inability to conduct offline transactions associated with traditional blockchains. This paper provides a detailed overview of the characteristics of the Tangle structure and the concepts applied in IOTA. Additionally, it explores potential approaches for integrating blockchain into IoT.

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“…Mining pools are among the most important actors in the Bitcoin ecosystem. They correspond to companies that regroup the activity of various miners-from individuals to mining farms-under a single entity, with the prospect of sharing the mining rewards obtained to mitigate the effect of chance on their source of revenue [30,33]. We chose mining pools because they are well-studied actors, persisting long enough in time, for which we can be confident in the data for validation.…”

Section: Taint Flows Of Bitcoin Mining Poolsmentioning

confidence: 99%

Pattern Analysis of Money Flows in the Bitcoin Blockchain

Tovanich

Cazabet

2023

Complex Networks and Their Applications XI

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Bitcoin is the first and highest valued cryptocurrency that stores transactions in a publicly distributed ledger called the blockchain. Understanding the activity and behavior of Bitcoin actors is a crucial research topic as they are pseudonymous in the transaction network. In this article, we propose a method based on taint analysis to extract taint flows-dynamic networks representing the sequence of Bitcoins transferred from an initial source to other actors until dissolution. Then, we apply graph embedding methods to characterize taint flows. We evaluate our embedding method with taint flows from top mining pools and show that it can classify mining pools with high accuracy. We also found that taint flows from the same period show high similarity. Our work proves that tracing the money flows can be a promising approach to classifying source actors and characterizing different money flow patterns.

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The Evolution of Mining Pools and Miners’ Behaviors in the Bitcoin Blockchain

Cited by 14 publications

References 23 publications

Bitcoin Revisited: Formalization, Benchmarking, and Open Security Issues

Bitcoin Revisited: Formalization, Benchmarking, and Open Security Issues

Improved DAG in blockchain tangle for IOTA

Pattern Analysis of Money Flows in the Bitcoin Blockchain

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