arXiv subjects

Kazuyuki Shudo

Publications and source records attributed to Kazuyuki Shudo.

At least 19 recordsLinked to original sources

arXiv2026

Near-Tight Theoretical Bounds for Incentive Compatibility in Bitcoin Mining

When is honest Bitcoin mining rational? This question is central to the incentive design of proof-of-work blockchains. Sapirshtein et al. computationally derived near-tight lower and upper bounds on the incentive-compatibility threshold using a Markov Decision Process. Kiayias et al.'s Blockchain Mining Games instead derived theoretical lower and upper bounds. However, this theoretical approach has two limitations: its model restricts miners to a narrow action space and assumes idealized tie behavior, and its lower and upper bounds are far from tight. We resolve both limitations. We develop a more realistic model with a broader miner action space and asymmetric tie-breaking parameters $γ^-$ and $γ^+$. We then propose an algorithm that computes lower and upper bounds on the incentive-compatibility threshold with a maximum error of $9.98006\times10^{-4}$.

cs.CR↗

arXiv2026

On the Incentive Compatibility of Block Propagation in Bitcoin

Bitcoin is permissionless and does not rely on any central administrator, which gives it strong censorship resistance. At the same time, it is important to incentivize miners to behave in ways that align with the interests of the system as a whole. This paper asks whether miners are individually incentivized to propagate blocks, one of the most fundamental processes in Bitcoin. Miners collectively maintain the blockchain by generating blocks and disseminating them across the network. If miners have an incentive not to propagate some blocks, this would indicate a fundamental flaw in Bitcoin's incentive design. Although prior work has studied how propagation delays affect forks and mining rewards, it has not fully characterized miners' incentives to improve block propagation under different tie-breaking rules. To address this gap, we derive analytical reward expressions for each tie-breaking rule based on a blockchain network model that captures the effect of forks on mining fairness. These expressions explicitly characterize how block propagation delays, hashrate distribution, and tie-breaking rules jointly determine mining rewards. We then use them to analyze miners' incentives to improve block propagation. Our results show, for example, that miners have no mining-reward incentive to relay blocks generated by other miners. By contrast, under the first-seen rule, every non-majority miner is incentivized to receive other miners' blocks more quickly and to propagate its own blocks more quickly. Finally, we compare tie-breaking rules and identify a trade-off between propagation incentives and mining fairness. In particular, the first-seen rule provides the strongest incentives to reduce propagation delays, but it also worsens mining fairness the most.

cs.CR↗

arXiv2025

Model-Based Calculation Method of Mining Fairness in Blockchain

Mining fairness in blockchain refers to equality between the computational resources invested in mining and the block rewards received. There exists a dilemma wherein increasing the transaction processing capacity of a blockchain compromises mining fairness, thereby undermining its decentralization. This dilemma remains unresolved despite methods such as the greedy heaviest observed subtree (GHOST) protocol, indicating that mining fairness is an inherent bottleneck in the transaction processing capacity of the blockchain system. However, despite its significance, existing analyses neglect the impact of blockchain forks, resulting in imprecise evaluations and limited insights. To address this issue, we propose a method for calculating mining fairness that explicitly captures the influence of forks. First, we approximate a complex blockchain network using a simple mathematical model, assuming that no more than two blocks are generated per round. Within this model, we quantitatively determine local mining fairness and derive several measures of global mining fairness based on local mining fairness. Subsequently, we validated by blockchain network simulations that our calculation method computes mining fairness in networks much more accurately than existing methods. The proposed method facilitates a rigorous evaluation of trade-offs between scalability and decentralization by offering a clear, quantitative framework for measuring and comparing reward distribution among miners. Consequently, it is expected to provide valuable insights for future mining fairness research and the design of next-generation blockchain systems.

cs.CR↗

arXiv2025

Clustering Coefficient Reflecting Pairwise Relationships within Hyperedges

Hypergraphs are generalizations of simple graphs that allow for the representation of complex group interactions beyond pairwise relationships. Clustering coefficients quantify local link density in networks and have been widely studied for both simple graphs and hypergraphs. However, existing clustering coefficients for hypergraphs treat each hyperedge as a distinct unit rather than a collection of potentially related node pairs, failing to capture intra-hyperedge pairwise relationships and incorrectly assigning zero values to nodes with meaningful clustering patterns. We propose a novel clustering coefficient that addresses this fundamental limitation by transforming hypergraphs into weighted graphs, where edge weights reflect relationship strength between nodes based on hyperedge connections. Our definition satisfies three key conditions: values in the range $[0,1]$, consistency with simple graph clustering coefficients, and effective capture of intra-hyperedge pairwise relationships -- a capability absent from existing approaches. Theoretical evaluation on higher-order motifs demonstrates that our definition correctly assigns values to motifs where existing definitions fail (motifs III, IV-a, IV-b of order 3), while empirical evaluation on three real-world datasets shows similar overall clustering tendencies with more detailed measurements, especially for hypergraphs with larger hyperedges. The proposed clustering coefficient enables accurate quantification of local density in complex networks, revealing structural characteristics missed by existing definitions in systems where group membership implies connections between members, such as social communities and co-authorship networks.

cs.DM↗

arXiv2025

The Rich Get Richer in Bitcoin Mining Induced by Blockchain Forks

Bitcoin is a representative decentralized currency system. For the security of Bitcoin, fairness in the distribution of mining rewards plays a crucial role in preventing the concentration of computational power in a few miners. Here, fairness refers to the distribution of block rewards in proportion to contributed computational resources. If miners with greater computational resources receive disproportionately higher rewards, i.e., if the Rich Get Richer (TRGR) phenomenon holds in Bitcoin, it indicates a threat to the system's decentralization. This study analyzes TRGR in Bitcoin by focusing on unintentional blockchain forks, an inherent phenomenon in Bitcoin. Previous research has failed to provide generalizable insights due to the low precision of their analytical methods. In contrast, we avoid this problem by adopting a method whose analytical precision has been empirically validated. The primary contribution of this work is a theoretical analysis that clearly demonstrates TRGR in Bitcoin under the assumption of fixed block propagation delays between different miners. More specifically, we show that the mining profit rate depends linearly on the proportion of hashrate. Furthermore, we examine the robustness of this result from multiple perspectives in scenarios where block propagation delays between different miners are not necessarily fixed.

cs.CR↗

arXiv2025

Comparing User Activity on X and Mastodon

The "Fediverse", a federation of decentralized social media servers, has emerged after a decade in which centralized platforms like X (formerly Twitter) have dominated the landscape. The structure of a federation should affect user activity, as a user selects a server to access the Fediverse and posts are distributed along the structure. This paper reports on the differences in user activity between Twitter and Mastodon, a prominent example of decentralized social media. The target of the analysis is Japanese posts because both Twitter and Mastodon are actively used especially in Japan. Our findings include a larger number of replies on Twitter, more consistent user engagement on mstdn.jp, and different topic preferences on each server.

cs.SI↗

arXiv2025

FiberPool: Leveraging Multiple Blockchains for Decentralized Pooled Mining

The security of blockchain systems based on Proof of Work relies on mining. However, mining suffers from unstable revenue, prompting many miners to form cooperative mining pools. Most existing mining pools operate in a centralized manner, which undermines the decentralization principle of blockchain. Distributed mining pools offer a practical solution to this problem. Well-known examples include P2Pool and SmartPool. However, P2Pool encounters scalability and security issues in its early stages. Similarly, SmartPool is not budget-balanced and imposes fees due to its heavy use of the smart contract. In this research, we present a distributed mining pool named FiberPool to address these challenges. FiberPool integrates a smart contract on the main chain, a storage chain for sharing data necessary for share verification, and a child chain to reduce fees associated with using and withdrawing block rewards. We validate the mining fairness, budget balance, reward stability, and incentive compatibility of the payment scheme FiberPool Proportional adopted by FiberPool.

cs.CR↗

arXiv2024

A Fully Local Last-Generated Rule in a Blockchain

An effective method for suppressing intentional forks in a blockchain is the last-generated rule, which selects the most recent chain as the main chain in the event of a chain tie. This rule helps invalidate blocks that are withheld by adversaries for a certain period. However, existing last-generated rules face an issue in that their applications to the system are not fully localized. In conservative cryptocurrency systems such as Bitcoin, it is desirable for methods to be applied in a fully local manner. In this paper, we propose a locally applicable last-generated rule. Our method is straightforward and is based on a relative time reference. By conservatively setting the upper bound for the clock skews $Δ_{O_i}$ to 200 s, our proposed method reduces the proportion $γ$ of honest miners following the attacker during chain ties by more than 40% compared to existing local methods.

cs.CR↗

arXiv2024

Estimation of Graph Features Based on Random Walks Using Neighbors' Properties

Using random walks for sampling has proven advantageous in assessing the characteristics of large and unknown social networks. Several algorithms based on random walks have been introduced in recent years. In the practical application of social network sampling, there is a recurrent reliance on an application programming interface (API) for obtaining adjacent nodes. However, owing to constraints related to query frequency and associated API expenses, it is preferable to minimize API calls during the feature estimation process. In this study, considering the acquisition of neighboring nodes as a cost factor, we introduce a feature estimation algorithm that outperforms existing algorithms in terms of accuracy. Through experiments that simulate sampling on known graphs, we demonstrate the superior accuracy of our proposed algorithm when compared to existing alternatives.

cs.SI↗

arXiv2024

Tie-Breaking Rule Based on Partial Proof of Work in a Blockchain

In the area of blockchain, numerous methods have been proposed for suppressing intentional forks by attackers more effectively than the random rule. However, all of them, except for the random rule, require major updates, rely on a trusted third party, or assume strong synchrony. Hence, it is challenging to apply these methods to existing systems such as Bitcoin. To address these issues, we propose another countermeasure that can be easily applied to existing proof of work blockchain systems. Our method is a tie-breaking rule that uses partial proof of work, which does not function as a block, as a time standard with finer granularity. By using the characteristic of partial proof of work, the proposed method enables miners to choose the last-generated block in a chain tie, which suppresses intentional forks by attackers. Only weak synchrony, which is already met by existing systems such as Bitcoin, is required for effective functioning. We evaluated the proposed method through a detailed analysis that is lacking in existing works. In networks that adopt our method, the proportion of the attacker hashrate necessary for selfish mining was approximately 0.31479 or higher, regardless of the block propagation capability of the attacker. Furthermore, we demonstrated through extended selfish mining that the impact of Match against pre-generated block, which is a concern in all last-generated rules, can be mitigated with appropriate parameter settings.

cs.CR↗

arXiv2023

Quantifying gender imbalance in East Asian academia: Research career and citation practice

Gender imbalance in academia has been confirmed in terms of a variety of indicators, and its magnitude often varies from country to country. Europe and North America, which cover a large fraction of research workforce in the world, have been the main geographical regions for research on gender imbalance in academia. However, the academia in East Asia, which accounts for a substantial fraction of research, may be exposed to strong gender imbalance because Asia has been facing persistent and stronger gender imbalance in society at large than Europe and North America. Here we use publication data between 1950 and 2020 to analyze gender imbalance in academia in China, Japan, and South Korea in terms of the number of researchers, their career, and citation practice. We found that, compared to the average of the other countries, gender imbalance is larger in these three East Asian countries in terms of the number of researchers and their citation practice and additionally in Japan in terms of research career. Moreover, we found that Japan has been exposed to the larger gender imbalance than China and South Korea in terms of research career and citation practice.

cs.DL↗

arXiv2023

Higher-order rich-club phenomenon in collaborative research grants

Modern scientific work, including writing papers and submitting research grant proposals, increasingly involves researchers from different institutions. In grant collaborations, it is known that institutions involved in many collaborations tend to densely collaborate with each other, forming rich clubs. Here we investigate higher-order rich-club phenomena in collaborative research grants among institutions and their associations with research productivity. Using publicly available data from the National Science Foundation in the US, we construct a bipartite network of institutions and collaborative grants, which distinguishes among the collaboration with different numbers of institutions. By extending the concept and algorithms of the rich club for dyadic networks to the case of bipartite networks, we find rich clubs both in the entire bipartite network and the bipartite subnetwork induced by the collaborative grants involving a given number of institutions up to five. We also find that the collaborative grants within rich clubs tend to be more productive in a per-dollar sense than the control. Our results highlight advantages of collaborative grants among the institutions in the rich clubs.

physics.soc-ph↗

arXiv2023

Randomizing hypergraphs preserving degree correlation and local clustering

Many complex systems involve direct interactions among more than two entities and can be represented by hypergraphs, in which hyperedges encode higher-order interactions among an arbitrary number of nodes. To analyze structures and dynamics of given hypergraphs, a solid practice is to compare them with those for randomized hypergraphs that preserve some specific properties of the original hypergraphs. In the present study, we propose a family of such reference models for hypergraphs, called the hyper dK-series, by extending the so-called dK-series for dyadic networks to the case of hypergraphs. The hyper dK-series preserves up to the individual node's degree, node's degree correlation, node's redundancy coefficient, and/or the hyperedge's size depending on the parameter values. We also apply the hyper dK-series to numerical simulations of epidemic spreading and evolutionary game dynamics on empirical hypergraphs.

physics.soc-ph↗

arXiv2023

Random Walk Sampling in Social Networks Involving Private Nodes

Analysis of social networks with limited data access is challenging for third parties. To address this challenge, a number of studies have developed algorithms that estimate properties of social networks via a simple random walk. However, most existing algorithms do not assume private nodes that do not publish their neighbors' data when they are queried in empirical social networks. Here we propose a practical framework for estimating properties via random walk-based sampling in social networks involving private nodes. First, we develop a sampling algorithm by extending a simple random walk to the case of social networks involving private nodes. Then, we propose estimators with reduced biases induced by private nodes for the network size, average degree, and density of the node label. Our results show that the proposed estimators reduce biases induced by private nodes in the existing estimators by up to 92.6% on social network datasets involving private nodes.

cs.SI↗

arXiv2022

Social Graph Restoration via Random Walk Sampling

Analyzing social graphs with limited data access is challenging for third-party researchers. To address this challenge, a number of algorithms that estimate structural properties via a random walk have been developed. However, most existing algorithms are limited to the estimation of local structural properties. Here we propose a method for restoring the original social graph from the small sample obtained by a random walk. The proposed method generates a graph that preserves the estimates of local structural properties and the structure of the subgraph sampled by a random walk. We compare the proposed method with subgraph sampling using a crawling method and the existing method for generating a graph that structurally resembles the original graph via a random walk. Our experimental results show that the proposed method more accurately reproduces the local and global structural properties on average and the visual representation of the original graph than the compared methods. We expect that our method will lead to exhaustive analyses of social graphs with limited data access.

cs.SI↗

arXiv2020

Trail: A Blockchain Architecture for Light Nodes

In Bitcoin and Ethereum, nodes require large storage capacity to maintain all the blockchain data, such as transactions, UTXOs, and account states. As of May 2020, the storage size of the Bitcoin blockchain has expanded to 270 GB, and it will continue to increase. This storage requirement is a major hurdle to becoming a block proposer or validator. Although many studies have attempted to reduce the storage size, in the proposed methods, a node cannot keep all blocks or cannot generate a block. We propose an architecture called Trail that allows nodes to hold all blocks in a small storage and to generate and validate blocks and transactions. Trail does not depend on a consensus algorithm or fork choice rule. In this architecture, a client who issues transactions has the data to prove its own balances and can generate a transaction containing the proof of balances. The nodes in Trail do not store transactions, UTXOs and account balances: they keep only blocks. The blocksize is approximately 8 KB, which is 100 times smaller than that of Bitcoin. Further, the block size is constant regardless of the number of accounts and the number of transactions. Compared to traditional blockchains, clients who issue transactions must store additional data. However, we show that proper data archiving can keep the account device storage size small. Trail allows more users to be block proposers and validators and improves the decentralization of the blockchain.

cs.DC↗

arXiv2020

Estimating Properties of Social Networks via Random Walk considering Private Nodes

Accurately analyzing graph properties of social networks is a challenging task because of access limitations to the graph data. To address this challenge, several algorithms to obtain unbiased estimates of properties from few samples via a random walk have been studied. However, existing algorithms do not consider private nodes who hide their neighbors in real social networks, leading to some practical problems. Here we design random walk-based algorithms to accurately estimate properties without any problems caused by private nodes. First, we design a random walk-based sampling algorithm that comprises the neighbor selection to obtain samples having the Markov property and the calculation of weights for each sample to correct the sampling bias. Further, for two graph property estimators, we propose the weighting methods to reduce not only the sampling bias but also estimation errors due to private nodes. The proposed algorithms improve the estimation accuracy of the existing algorithms by up to 92.6% on real-world datasets.

cs.SI↗

arXiv2020

Identifying Impacts of Protocol and Internet Development on the Bitcoin Network

Improving transaction throughput is an important challenge for Bitcoin. However, shortening the block generation interval or increasing the block size to improve throughput makes it sharing blocks within the network slower and increases the number of orphan blocks. Consequently, the security of the blockchain is sacrificed. To mitigate this, it is necessary to reduce the block propagation delay. Because of the contribution of new Bitcoin protocols and the improvements of the Internet, the block propagation delay in the Bitcoin network has been shortened in recent years. In this study, we identify impacts of compact block relay---an up-to-date Bitcoin protocol---and Internet improvement on the block propagation delay and fork rate in the Bitcoin network from 2015 to 2019. Existing measurement studies could not identify them but our simulation enables it. The experimental results reveal that compact block relay contributes to shortening the block propagation delay more than Internet improvements. The block propagation delay is reduced by 64.5% for the 50th percentile and 63.7% for the 90th percentile due to Internet improvements, and by 90.1% for the 50th percentile and by 87.6% for the 90th percentile due to compact block relay.

cs.DC↗