Abstract
In this paper, we first present a theoretical analysis model on the Proof-of-Work (PoW) for cryptocurrency blockchain. Based on this analysis, we present a new type of PoW, which relies on the hardness of solving a set of random quadratic equations over the finite field GF(2). We will present the advantages of such a PoW, in particular, in terms of its impact on decentralization and the incentives involved, and therefore demonstrate that this is a new good alternative as a new type for PoW in blockchain applications.
Original language | English |
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Title of host publication | Applied Cryptography and Network Security Workshops - ACNS 2019 Satellite Workshops, SiMLA, Cloud S and P, AIBlock, and AIoTS 2019 |
Editors | Jianying Zhou, Robert Deng, Zhou Li, Suryadipta Majumdar, Weizhi Meng, Lingyu Wang, Kehuan Zhang |
Publisher | Springer Verlag |
Pages | 97-107 |
Number of pages | 11 |
ISBN (Print) | 9783030297282 |
DOIs | |
Publication status | Published - 2019 |
Externally published | Yes |
Event | 17th International Conference on Applied Cryptography and Network Security, ACNS 2019 - Bogota, Colombia Duration: 5 Jun 2019 → 7 Jun 2019 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 11605 LNCS |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | 17th International Conference on Applied Cryptography and Network Security, ACNS 2019 |
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Country/Territory | Colombia |
City | Bogota |
Period | 5/06/19 → 7/06/19 |
Keywords
- Blockchain
- Cryptocurrency
- Decentralization
- Multivariate
- NP-hard
- Proof-of-Work
- Quadratic
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Ding, J. (2019). A New Proof of Work for Blockchain Based on Random Multivariate Quadratic Equations. In J. Zhou, R. Deng, Z. Li, S. Majumdar, W. Meng, L. Wang, & K. Zhang (Eds.), Applied Cryptography and Network Security Workshops - ACNS 2019 Satellite Workshops, SiMLA, Cloud S and P, AIBlock, and AIoTS 2019 (pp. 97-107). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11605 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-29729-9_5