Double Spending Analysis of Nakamoto Consensus for Time-Varying Mining Rates with Ruin Theory

Theoretical guarantees for double spending probabilities for the Nakamoto consensus under the k-deep confirmation rule have been extensively studied for zero/bounded network delays and fixed mining rates. In this paper, we introduce a ruin-theoretical model of double spending for Nakamoto consensus under the k-deep confirmation rule when the honest mining rate is allowed to be an arbitrary function of time including the block delivery periods, i.e., time periods during which mined blocks are being delivered to all other participants of the network. Time-varying mining rates are considered to capture the intrinsic characteristics of the peer to peer network delays as well as dynamic participation of miners such as the gap game and switching between different cryptocurrencies. Ruin theory is leveraged to obtain the double spend probabilities and numerical examples are presented to validate the effectiveness of the proposed analytical method.

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Publication Details

Published
2025-06-02
DOI
https://doi.org/10.1109/icbc64466.2025.11114481
Citations
1
Primary Topic
Bladder and Urothelial Cancer Treatments
Type
article
Field-Weighted Citation Impact
2.01
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Double Spending Analysis of Nakamoto Consensus for Time-Varying Mining Rates with Ruin Theory

1 citations
Bladder and Urothelial Cancer Treatments
2.01
article

Double Spending Analysis of Nakamoto Consensus for Time-Varying Mining Rates with Ruin Theory

article en
1 citations

Abstract

Theoretical guarantees for double spending probabilities for the Nakamoto consensus under the k-deep confirmation rule have been extensively studied for zero/bounded network delays and fixed mining rates. In this paper, we introduce a ruin-theoretical model of double spending for Nakamoto consensus under the k-deep confirmation rule when the honest mining rate is allowed to be an arbitrary function of time including the block delivery periods, i.e., time periods during which mined blocks are being delivered to all other participants of the network. Time-varying mining rates are considered to capture the intrinsic characteristics of the peer to peer network delays as well as dynamic participation of miners such as the gap game and switching between different cryptocurrencies. Ruin theory is leveraged to obtain the double spend probabilities and numerical examples are presented to validate the effectiveness of the proposed analytical method.

Bilkent University (TR), University of Maryland, College Park (US)
Decent work and economic growth
Openalex Percentile: Top 10%
Bladder and Urothelial Cancer Treatments
2.01
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