HashCore: Proof-of-Work Functions for General Purpose Processors

被引:6
作者
Georghiades, Yanni [1 ]
Flolid, Steven [1 ]
Vishwanath, Sriram [1 ]
机构
[1] Univ Texas Austin, Dept ECE, Austin, TX 78712 USA
来源
2019 39TH IEEE INTERNATIONAL CONFERENCE ON DISTRIBUTED COMPUTING SYSTEMS (ICDCS 2019) | 2019年
关键词
Blockchain; Proof-of-Work; Mining; Security; Cryptography; Collision-Resistant Hash Function;
D O I
10.1109/ICDCS.2019.00193
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Over the past five years, the rewards associated with mining Proof-of-Work blockchains have increased substantially. As a result, miners are heavily incentivized to design and utilize Application Specific Integrated Circuits (ASICs) that can compute hashes far more efficiently than existing general purpose hardware. Currently, it is difficult for most users to purchase and operate ASICs due to pricing and availability constraints, resulting in a relatively small number of miners with respect to total user base for most popular cryptocurrencies. In this work, we aim to invert the problem of ASIC development by constructing a Proof-of-Work function for which an existing general purpose processor (GPP, such as an x86 IC) is already an optimized ASIC. In doing so, we will ensure that any would-be miner either already owns an ASIC for the Proof-of-Work system they wish to participate in or can attain one at a competitive price with relative ease. In order to achieve this, we present HashCore, a Proof-of-Work function composed of "widgets" generated pseudo-randomly at runtime that each execute a sequence of general purpose processor instructions designed to stress the computational resources of such a GPP. The widgets will be modeled after workloads that GPPs have been optimized for, for example, the SPEC CPU 2017 benchmark suite for x86 ICs, in a technique we refer to as inverted benchmarking. We provide a proof that HashCore is collision-resistant regardless of how the widgets are implemented. We observe that GPP designers/developers essentially create an ASIC for benchmarks such as SPEC CPU 2017. By modeling HashCore after such benchmarks, we create a Proof-of-Work function that can be run most efficiently on a GPP, resulting in a more accessible, competitive, and balanced mining market.
引用
收藏
页码:1951 / 1959
页数:9
相关论文
共 50 条
  • [41] Proof-of-Work Explained in VR: A Case Study
    Keller, Thomas
    Gamperli, Michael
    Brucker-Kley, Elke
    EXTENDED REALITY, PT I, XR SALENTO 2024, 2024, 15027 : 114 - 129
  • [42] Securing Proof-of-Work Ledgers via Checkpointing
    Karakostas, Dimitris
    Kiayias, Aggelos
    2021 IEEE INTERNATIONAL CONFERENCE ON BLOCKCHAIN AND CRYPTOCURRENCY (ICBC), 2021,
  • [43] On the Application of Clique Problem for Proof-of-Work in Cryptocurrencies
    Bag, Samiran
    Ruj, Sushmita
    Sakurai, Kouichi
    INFORMATION SECURITY AND CRYPTOLOGY, INSCRYPT 2015, 2016, 9589 : 260 - 279
  • [44] Evaluation of Hash Rate-based Double-Spending based on Proof-of-Work Blockchain
    Suliyanti, Widya Nita
    Sari, Riri Fitri
    2019 10TH INTERNATIONAL CONFERENCE ON INFORMATION AND COMMUNICATION TECHNOLOGY CONVERGENCE (ICTC): ICT CONVERGENCE LEADING THE AUTONOMOUS FUTURE, 2019, : 169 - 174
  • [45] Catfish Effect Between Selfish Miners in Proof-of-Work Based Blockchain
    Ruan N.
    Liu H.-Q.
    Si X.-M.
    Jisuanji Xuebao/Chinese Journal of Computers, 2021, 44 (01): : 177 - 192
  • [47] The impact of propagation delay to different selfish miners in proof-of-work blockchains
    Heli Wang
    Qiao Yan
    Victor C. M. Leung
    Peer-to-Peer Networking and Applications, 2021, 14 : 2735 - 2742
  • [48] Improving the performance of the Proof-of-Work Consensus Protocol Using Machine learning
    Safana, Mujistapha Ahmed
    Arafa, Yasmine
    Ma, Jixin
    2020 SECOND INTERNATIONAL CONFERENCE ON BLOCKCHAIN COMPUTING AND APPLICATIONS (BCCA), 2020, : 16 - 21
  • [49] The impact of propagation delay to different selfish miners in proof-of-work blockchains
    Wang, Heli
    Yan, Qiao
    Leung, Victor C. M.
    PEER-TO-PEER NETWORKING AND APPLICATIONS, 2021, 14 (05) : 2735 - 2742
  • [50] Genetic-Algorithm-Inspired Difficulty Adjustment for Proof-of-Work Blockchains
    Chin, Zi Hau
    Yap, Timothy Tzen Vun
    Tan, Ian Kim Teck
    SYMMETRY-BASEL, 2022, 14 (03):