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所在平台: Udemy |
课程主页: https://www.udemy.com/course/introduction-to-secure-multi-party-computation-smpc/
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课程名称：安全多方计算（SMPC）导论 课程概述：欢迎参加“安全多方计算导论”课程。在信息时代，动态决策常常是组织防御的第一道防线。然而，决策不仅需要基于组织内部运作，还需要考虑宏观环境。这就是为什么组织需要以行业财团或网络的形式进行合作，并且这通常涉及数据共享。然而，数据共享也带来了隐私问题。此外，诸如欧洲的GDPR和美国的HIPAA等法规要求组织确保敏感数据的隐私和安全。随着区块链和分布式计算等去中心化技术的兴起，对安全和隐私保护计算协议的需求日益增加。这就是安全多方计算（SMPC）的作用所在。SMPC允许多个参与方之间进行协作的数据分析、计算和机器学习，同时通过加密协议和技术保持数据的隐私和机密性。如果您对理论方面更感兴趣，请参考课程讲座中附带的论文。祝您学习顺利！
Welcome to the "Introduction to Secure Multi-party Computation (SMPC)". In the age of information, dynamic decision making is often the first line of defence for organizations. But, the decision making has to be informed not only on the internal workings of the organization but also on the macro environment.This is why organizations need to collaborate among in the form of industry consortiums or networks themselves and this often involves data sharing.Apart from decision making, data sharing is often a requirement for various members of the same value chain say financial intermediaries or manufacturers, assemblers, and distributors.But, data sharing comes with own caveat - privacy concerns. Apart from privacy concerns, various regulations such as GDPR in Europe and HIPAA in the United States requires organizations to ensure the privacy and security of sensitive data.Also, with the rise of decentralized technologies such as blockchain and distributed computing, there is a growing need for secure and privacy-preserving computation protocols.This is where Secure Multi-Party Computation or SMPC comes in.Secure Multi-Party Computation (SMPC) enables collaborative data analysis, computation, and machine learning across multiple parties while preserving data privacy and confidentiality through cryptographic protocols and techniques.If you are more theoretically inclined, please refer to the papers attached to the lectures.All the best.
