NDSS

Constructing an Adversary Solver for Equihash

Xiaofei Bai (School of Computer Science, Fudan University), Jian Gao (School of Computer Science, Fudan University), Chenglong Hu (School of Computer Science, Fudan University), Liang Zhang (School of Computer Science, Fudan University)

Blockchain networks, especially cryptocurrencies, rely heavily on proof-of-work (PoW) systems, often as a basis to distribute rewards. These systems require solving specific puzzles, where Application Specific Integrated Circuits (ASICs) can be designed for performance or efficiency. Either way, ASICs surpass CPUs and GPUs by orders of magnitude, and may harm blockchain networks. Recently, Equihash is developed to resist ASIC solving with heavy memory usage. Although commercial ASIC solvers exist for its most popular parameter set, such solvers do not work under better ones, and are considered impossible under optimal parameters. In this paper, we inspect the ASIC resistance of Equihash by constructing a parameter-independent adversary solver design. We evaluate the product, and project at least 10x efficiency advantage for resourceful adversaries. We contribute to the security community in two ways: (1) by revealing the limitation of Equihash and raising awareness about its algorithmic factors, and (2) by demonstrating that security inspection is practical and useful on PoW systems, serving as a start point for future research and development.