In this episode, we discuss the topic of secure multi-party computation. Since its introduction in the eighties, secure multi-party computation – also known as SMPC – has evolved into a subfield of cryptography for which a variety of protocols have been developed. SMPC is a technique used to allow multiple parties to jointly compute a function on their private inputs without revealing any information about those inputs to the other parties.
Liz Acosta, Developer Advocate at Skyflow, joins the show to explain SMPC and share her recent research into the subject. We begin by explaining the basic concept of SMPC and how it differs from traditional methods of computation.
We also discuss the practical applications of SMPC, such as in the financial industry for secure trading and in the healthcare industry for secure sharing of patient data. We also highlight the challenges that still need to be addressed in the field, such as scalability and ensuring the security of the computation.

Topics:
What is Yao’s millionaire problem and how does it relate to secure multi-party computation?
Can you explain what secure multi-party computation is and how it works?
Where did this concept come from? What’s the history?
Can you walk me through an example of using SMPC to solve a problem?
In what types of scenarios is secure multi-party computation particularly useful?
How is secure multi-party computation being used in the real world today?
How does secure multi-party computation enable collaboration while still preserving the privacy of individual parties?
What are the challenges and opportunities for the wider adoption of secure multi-party computation in the future?
How far away do you think we are from secure multi-party computation being more widely adopted?
Beyond SMPC, are there technologies in this space that you are particularly excited about?
Where should someone look to learn more about secure multi-party computation or other privacy-enhancing technologies

Resources:
What is Secure Multi-Party Computation?