Since the initial proposal of Zero-Knowledge Proofs in the 1980s by researchers Shafi Goldwasser, Silvio Micali, and Charles Rackoff, the development of Zero-Knowledge (ZK) technology has significantly evolved. Today, these groundbreaking cryptographic techniques have the potential to revolutionize privacy, security, and trust across various domains; perhaps particularly regarding decentralized systems and applications.
The basic cryptographic components within the application of ZK:
Prover The entity that knows the secret information and wants to prove that they possess certain knowledge without revealing the actual information.
Verifier The entity that verifies the proof provided by the prover. The verifier ensures the proof is correct without learning the actual secret.
Zero-Knowledge Proof (ZKP) can handle various domains of privacy by allowing one party (the prover) to prove to another party (the verifier) that a statement is true without revealing any information beyond the validity of the statement itself.
Completeness means that if a prover can claim a result, they can produce a proof that the verifier will accept.
Soundness ensures that a verifier only accepts a proof if the statement is true. In other words, the verifier only accepts a computation's result if valid inputs can be provided that lead to that result.
Succinctness refers to the size of the proofs and the time and space needed to verify them.
Interactive and Non-Interactive ZKPs:
Interactive ZKP Requires multiple rounds of communication between the prover and verifier.
Non-Interactive ZKP proof is generated and sent in a single communication round, often using the Fiat-Shamir heuristic.
To accelerate the growth of ZK applications, new frameworks are being developed to support additional production-level features. High-performance frameworks such as zkVM’s like zkMIPS demonstrate both efficiency and significant potential, empowering developers to create a wide range of real-world applications, including enterprise-grade privacy solutions.
ZK is ever-evolving, and by leveraging special tools, libraries and infrastructures such as zkVMs, zkEVMs, and ZK co-processors, developers are provided with accessible, versatile and highly programmable solutions for building diverse classes of applications.
These frameworks utilize interactive proof systems like ZKP’s to execute smart contracts or other computational tasks while potentially preserving privacy.
A Zero Knowledge Virtual Machine is a program that can run other programs, implemented as a circuit for a ZKP system. They’re designed primarily for use in blockchain and related technologies to facilitate verifiable computation and secure communication channels, ensuring the integrity and consistency of data across different platforms.
ZKM developed a zkVM, called zk-MIPS, capable of verifying on-chain that a
“Microprocessor without Interlocked Pipeline Stages” (MIPS) program was correctly executed off-chain. Specifically, MIPS is a minimalistic architecture for microprocessors that aims for simplicity. Any higher-level code written gets compiled into a small set of different instructions, ready for execution by the MIPS VM.
Because the MIPS architecture is so minimal, converting high-level code to MIPS is relatively straightforward, and since most programming languages can be easily compiled to MIPS, zKMIPS supports a wide range of programs, enabling zkMIPS to verify the correctness of blockchain transactions, smart contract function calls and rollups.
zkMIPS has multiple potential functions, for example:
Co-processing: by offloading certain computational tasks from the main processor, transforming all of the computation into a different format that is suitable for processing with ZK.
Scalability Solutions: zkMIPS enables bundling of multiple transactions into a single transaction, generating a ZKP that proves the correctness of all bundled transactions.
Interoperability: By generating a proof of an execution on one blockchain and verifying on another, zkMIPS presents an optimal solution for creating an interoperable blockchain environment in a completely secure and decentralized way.
Data Minimization: This is a principle that aims to limit the amount of personal data collected, processed, and stored. zkMIPS has the potential to use a privacy-enhancing technique that leverages ZKPs to minimize the amount of data shared or revealed during a transaction or interaction.
The Benefit of Open-Source for Zero-Knowledge Scaling
Open-source is a proficient way to onboarding Zero Knowledge applications.
The nonprofit open-source initiative sets other stipulations and standards, enabling adaptability, cross-platform integration, Security, cost-minimization and further innovations.
ZKM aims to be a fully open-source project, focusing on research to advance verifiable computing to the degree of being able to provide a completely integrated and seamless blockchain experience to create a fully decentralized and trustworthy internet, leveraging its zkVM technology and robust proving service.
