稳健,是 Gate 持续增长的核心动力。
真正的成长,不是顺风顺水,而是在市场低迷时依然坚定前行。我们或许能预判牛熊市的大致节奏,但绝无法精准预测它们何时到来。特别是在熊市周期,才真正考验一家交易所的实力。
Gate 今天发布了2025年第二季度的报告。作为内部人,看到这些数据我也挺惊喜的——用户规模突破3000万,现货交易量逆势环比增长14%,成为前十交易所中唯一实现双位数增长的平台,并且登顶全球第二大交易所;合约交易量屡创新高,全球化战略稳步推进。
更重要的是,稳健并不等于守成,而是在面临严峻市场的同时,还能持续创造新的增长空间。
欢迎阅读完整报告:https://www.gate.com/zh/announcements/article/46117
MPC and Blockchain Cryptography: A Deep Dive
Multiparty computation (MPC) and blockchain are both distributed systems. This article serves as a learning note (a directory entry) on cryptography, MPC, and blockchain.
Symmetric encryption, asymmetric encryption, and hash functions basically constitute all levels of cryptographic algorithms.
Cryptographic protocols include:
A key concept in MPC is simulation, which means bringing the hypothetical world of the ideal into the real world (especially with regard to trust). Six important characteristics that need to be considered are:
Based on different levels of untrustworthiness, there are several security models in cryptography:
Garbled circuits (GC) and oblivious transfer (OT) are two protocols that are suitable for logical operations but not arithmetic operations. They are mostly studied between two parties rather than multiple parties (although many people are researching how to convert 2PC into MPC).
The bottom-level technology of MPC is secret sharing (SS), which essentially involves taking some points to fit a curve. It is more suitable for linear operations such as addition, but not for multiplication. Multiplication is also a major challenge when constructing MPC. SS has advanced to include verifiable secret sharing (VSS) and publicly verifiable secret sharing (pVSS). pVSS can be understood from a cryptographic perspective as a blockchain, but there is currently no mature solution.
The difficulty of completing digital signatures with MPC lies in how to use TSS to complete an asymmetric encryption.
Digital signatures:
In summary, MPC is a cryptographic technique that enables multiple parties to collaborate on a computation without revealing their private inputs. It is a crucial tool for achieving privacy-preserving distributed computation and can be applied to many fields, such as secure machine learning, secure computation outsourcing, and privacy-preserving data analysis. Note: this article is a translation and summary for easier reading of a Twitter thread by 0x30cF.