A few designs have taken into account circuit-based functional descriptions in order to solve the problems with widespread adoption that cryptosystems encounter. Theoretically, a cryptosystem can be used to general-purpose computational issues if its fundamental modules can simulate a Turing computer. Programmable cryptography is the term for this method, which uses circuit specifications to describe cryptosystems.

In another groundbreaking application, programmable cryptography facilitates the confidential calculation of credit scores from a user’s interactions with web2 services, like social media, without exposing specific activities. This enables a privacy-centric assessment of creditworthiness, revolutionizing the evaluation of financial trustworthiness in today’s digital world.

For practical applications, theoretical viability is far from sufficient. Practical implementation of such a cryptosystem is unfeasible once its complexity increases too rapidly with the size of the computational issue. To close the knowledge gap between theory and practice, cryptographers are always improving these methods. Creating new frameworks, refining engineering implementations, and optimising underlying primitives are all part of this approach.

There are several advantages to programmable cryptography. First of all, it greatly increases the adaptability and flexibility of cryptography's practical applications. Additionally, programmability makes applied cryptography more accessible to a worldwide developer community, encouraging experimentation and creativity, rather than remaining a specialised field for only a small number of academics.

Cryptography is essentially just the act of sending private messages between entities. A few requirements are introduced by the act: messages can be understood by the sender and recipient, but they might not be understood by a third party interceptor. Crucially, it must also guarantee that the message cannot be altered before to delivery. Digital signatures, for example, offer integrity and authentication for communication via unsecure networks.

The necessity to safeguard various types of online data and messages during storage, transport, and calculation is currently addressed by sophisticated cryptographic systems. These include blockchain, e-commerce, banking, and auctions, to mention a few. Among these systems are fully homomorphic encryption (FHE), multi-party computation (MPC), and zero-knowledge proofs (ZKP). Based on mathematics, each of these systems caters to particular situations and requirements.

MPC protects input data privacy in scenarios where multiple parties perform collaborative computations. One use case for MPC is institutional custody, which firms such as Fireblocks use, enabling the segregation of responsibility between individuals overseeing a wallet. ZKPs efficiently enable verifiable computation and data privacy in single-party contexts and are currently used in blockchain privacy and scaling.

The development of sophisticated cryptographic systems has opened up many fascinating opportunities for the digital world, but it has also presented substantial obstacles. For a long time, people could only use specialised cryptographic protocols made for particular uses, like private intersections, private voting and auctions, and physical identity verification. It is not easy to make these systems function in the actual world. Cryptographers have to prepare everything extremely carefully, including performance optimisation, primitive choice making, and security assumptions. This intricacy restricts the extensive use of cryptosystems. A key component of transferring cryptography from theory to practice is the capacity to effectively execute a protocol in a broader setting.