### 抄録

Recently, Bitcoin is becoming one of the most popular decentralized cryptographic currency technologies, and Bitcoin mining is a process of adding transaction records to Bitcoin’s public ledger of past transactions or blockchain. To obtain a bitcoin, the mining process involves compiling recent transactions into blocks and trying to solve a computationally difficult puzzle, e.g., proof of work puzzle. A proof of work allows miners the ability to quantify how much work a given proof contains. Basically, the required time for mining is decided in advance, but problems will occur if the value is large for dispersion. In this paper, we first accept that the required time between consecutive blocks follows the exponential distribution. That is, the variance is stable as long as the expected time is fixed. Then, we focus on the graph clique mining technique proposed by the literature, like Tromp (BITCOIN 2015) and Bag-Ruj-Sakurai (Inscrypt 2015), which is based on a computational difficulty problem of searching cliques of undirected graphs, where a clique is a subset of vertices. In particular, when the clique size is two, graph clique mining can be used to gain Bitcoins. The previous work also claimed that if the clique size is parameterized and increased, even if the expected time is fixed, the variance would not be stable. However, no qualitative or quantitative results were given to support their claim. Motivated by this issue, in this work, we propose a simple search algorithm for graph cliques mining, and perform a small scale evaluation on Bitcoin and Graph cliques’s solo mining to investigate the variance issue.

元の言語 | 英語 |
---|---|

ホスト出版物のタイトル | Information Security and Cryptology - 14th International Conference, Inscrypt 2018, Revised Selected Papers |

編集者 | Moti Yung, Xinyi Huang, Fuchun Guo |

出版者 | Springer Verlag |

ページ | 101-114 |

ページ数 | 14 |

ISBN（印刷物） | 9783030142339 |

DOI | |

出版物ステータス | 出版済み - 1 1 2019 |

イベント | 14th International Conference on Information Security and Cryptology, Inscrypt 2018 - Fuzhou, 中国 継続期間: 12 14 2018 → 12 17 2018 |

### 出版物シリーズ

名前 | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
---|---|

巻 | 11449 LNCS |

ISSN（印刷物） | 0302-9743 |

ISSN（電子版） | 1611-3349 |

### 会議

会議 | 14th International Conference on Information Security and Cryptology, Inscrypt 2018 |
---|---|

国 | 中国 |

市 | Fuzhou |

期間 | 12/14/18 → 12/17/18 |

### Fingerprint

### All Science Journal Classification (ASJC) codes

- Theoretical Computer Science
- Computer Science(all)

### これを引用

*Information Security and Cryptology - 14th International Conference, Inscrypt 2018, Revised Selected Papers*(pp. 101-114). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 巻数 11449 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-14234-6_6

**Analysis of variance of graph-clique mining for scalable proof of work.** / Anada, Hiroaki; Matsushima, Tomohiro; Su, Chunhua; Meng, Weizhi; Kawamoto, Junpei; Bag, Samiran; Sakurai, Kouichi.

研究成果: 著書/レポートタイプへの貢献 › 会議での発言

*Information Security and Cryptology - 14th International Conference, Inscrypt 2018, Revised Selected Papers.*Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 巻. 11449 LNCS, Springer Verlag, pp. 101-114, 14th International Conference on Information Security and Cryptology, Inscrypt 2018, Fuzhou, 中国, 12/14/18. https://doi.org/10.1007/978-3-030-14234-6_6

}

TY - GEN

T1 - Analysis of variance of graph-clique mining for scalable proof of work

AU - Anada, Hiroaki

AU - Matsushima, Tomohiro

AU - Su, Chunhua

AU - Meng, Weizhi

AU - Kawamoto, Junpei

AU - Bag, Samiran

AU - Sakurai, Kouichi

PY - 2019/1/1

Y1 - 2019/1/1

N2 - Recently, Bitcoin is becoming one of the most popular decentralized cryptographic currency technologies, and Bitcoin mining is a process of adding transaction records to Bitcoin’s public ledger of past transactions or blockchain. To obtain a bitcoin, the mining process involves compiling recent transactions into blocks and trying to solve a computationally difficult puzzle, e.g., proof of work puzzle. A proof of work allows miners the ability to quantify how much work a given proof contains. Basically, the required time for mining is decided in advance, but problems will occur if the value is large for dispersion. In this paper, we first accept that the required time between consecutive blocks follows the exponential distribution. That is, the variance is stable as long as the expected time is fixed. Then, we focus on the graph clique mining technique proposed by the literature, like Tromp (BITCOIN 2015) and Bag-Ruj-Sakurai (Inscrypt 2015), which is based on a computational difficulty problem of searching cliques of undirected graphs, where a clique is a subset of vertices. In particular, when the clique size is two, graph clique mining can be used to gain Bitcoins. The previous work also claimed that if the clique size is parameterized and increased, even if the expected time is fixed, the variance would not be stable. However, no qualitative or quantitative results were given to support their claim. Motivated by this issue, in this work, we propose a simple search algorithm for graph cliques mining, and perform a small scale evaluation on Bitcoin and Graph cliques’s solo mining to investigate the variance issue.

AB - Recently, Bitcoin is becoming one of the most popular decentralized cryptographic currency technologies, and Bitcoin mining is a process of adding transaction records to Bitcoin’s public ledger of past transactions or blockchain. To obtain a bitcoin, the mining process involves compiling recent transactions into blocks and trying to solve a computationally difficult puzzle, e.g., proof of work puzzle. A proof of work allows miners the ability to quantify how much work a given proof contains. Basically, the required time for mining is decided in advance, but problems will occur if the value is large for dispersion. In this paper, we first accept that the required time between consecutive blocks follows the exponential distribution. That is, the variance is stable as long as the expected time is fixed. Then, we focus on the graph clique mining technique proposed by the literature, like Tromp (BITCOIN 2015) and Bag-Ruj-Sakurai (Inscrypt 2015), which is based on a computational difficulty problem of searching cliques of undirected graphs, where a clique is a subset of vertices. In particular, when the clique size is two, graph clique mining can be used to gain Bitcoins. The previous work also claimed that if the clique size is parameterized and increased, even if the expected time is fixed, the variance would not be stable. However, no qualitative or quantitative results were given to support their claim. Motivated by this issue, in this work, we propose a simple search algorithm for graph cliques mining, and perform a small scale evaluation on Bitcoin and Graph cliques’s solo mining to investigate the variance issue.

UR - http://www.scopus.com/inward/record.url?scp=85064121196&partnerID=8YFLogxK

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U2 - 10.1007/978-3-030-14234-6_6

DO - 10.1007/978-3-030-14234-6_6

M3 - Conference contribution

SN - 9783030142339

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 101

EP - 114

BT - Information Security and Cryptology - 14th International Conference, Inscrypt 2018, Revised Selected Papers

A2 - Yung, Moti

A2 - Huang, Xinyi

A2 - Guo, Fuchun

PB - Springer Verlag

ER -