A glimpse at the emerging ZK use cases: zkML, ZK games, ZK ID

Original title: “Emerging ZK Use Cases”

Original author: zkvalidator

Compilation of the original text: Kate

In this article, we explore emerging ZK use cases.

introduce

In the past few months, we have witnessed a lot of hype surrounding zero-knowledge use cases, including zkevm, zkBridges, and more. However, in such a fast-paced environment, new use cases are emerging where zero-knowledge proofs (ZKPs) play a vital role. This article aims to explore areas where ZKPs are gaining more attention in the minds of individuals.

ZKML Zero Knowledge Machine Learning

This diagram shows how zkML works

ZKML (Zero-Knowledge Machine Learning) is an emerging technology with huge potential in various applications that has not yet been fully exploited. ZKML opens new doors for innovation, from computational integrity and privacy protection to machine learning-as-a-service transparency and decentralized inference or training. Here are some potential use cases for ZKML:

Verifiability of ZKML: ZKML leverages validity proofs such as SNARKs and STARKs to ensure accurate execution of computations, especially in machine learning. By using these proofs, machine learning model reasoning can be verified to confirm the origin of the output given the input. This feature allows machine learning models to be deployed off-chain while ZK proofs are conveniently verified on-chain.

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Privacy Preservation in ZKML: Privacy is a critical issue in machine learning, and ZKML provides a solution. It can prove the accuracy of the model on the test data without revealing the weights used, thus ensuring data privacy. Additionally, ZKML facilitates privacy-preserving reasoning, allowing sensitive medical diagnoses, such as cancer test results, to be shared with patients without leaking their data to third parties.

Enhancing the transparency of ML-as-a-Service: ZKML plays a vital role in increasing the transparency of ML-as-a-Service. By providing proof of validity associated with the Machine Learning Model API, users can verify the authenticity of the models they use. This solves problems associated with legacy APIs (often viewed as black boxes) and increases trust in the provided model.

Decentralized inference and training: ZKML can perform machine learning tasks in a decentralized manner. The model can be compressed by utilizing zero-knowledge proofs, allowing public participation and data submission during inference or training. This opens new avenues for collaborative and distributed machine learning.

ZKML Proofs: Proofs are an important aspect of ZKML, allowing verifiable proofs to be incorporated from trusted external parties. By using zero-knowledge proofs to verify digital signatures from trusted sources, ZKML ensures the authenticity and origin of attested information. This allows trusted references to be verified and used in various applications.

Application of ZK in games

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Zero Knowledge Proofs (ZKP) offer many advantages for game architecture and game experience. By integrating ZKP, game developers can benefit from cost reduction, enhanced privacy protection, effective anti-cheat measures, and improved scalability.

In terms of game architecture, ZKP has a major impact on online multiplayer games by minimizing sensitive data stored on centralized servers, thereby reducing the cost of maintaining client-server architecture. Additionally, ZKP enhances the privacy and security of peer-to-peer (P2P) gaming systems, eliminating the need for expensive servers while ensuring the authenticity of in-game events and preventing cheating.

ZKPs also address game scalability challenges by reducing server overhead in client-server architectures and enabling verifiable proofs of game operations in P2P multiplayer games. This expands the number of concurrent players that can be supported, resulting in a more enjoyable gaming experience and appealing to a wider player base.

As far as gameplay is concerned, ZKPs provide solutions for various game types. In first-person shooters (FPS), ZKPs can verify player skill levels without revealing sensitive information, thereby improving matching accuracy. In massively multiplayer online role-playing games (MMORPGs), ZKPs enable secure ownership and exchange of virtual assets, creating a unified economy across different games. ZKPs also have applications in gambling and casino games, providing verifiably random outcomes and protecting player privacy. Additionally, ZKPs can secure player progress and high scores in puzzle and strategy games while keeping sensitive information private.

The adoption of ZKP in the game industry can improve the game experience, improve player stickiness and obtain higher profits. As the use of ZKPs expands, specialized hardware may become critical to meet the growing demand for computing power.

ZK ID - Decentralized ID

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Establishing digital trust and secure authentication is critical in today’s online environment. The advent of Zero-Knowledge Proofs (ZKP) has revolutionized the field by providing greater privacy and security. Here, we explore the properties and advantages of zero-knowledge proofs, and their potential to redefine digital identity verification.

• Enhanced privacy protection: Zero-knowledge proofs are excellent at protecting sensitive information. Users can verify their identity or credentials without revealing specific details such as personal identification numbers or addresses. ZKPs establish a security framework that allows trustless interactions while maintaining confidentiality.
• Secure and verifiable interactions: Zero-knowledge proofs enable users to participate in smart contracts and verify information on the blockchain while hiding their private data. Off-chain credentials like passports or educational degrees can generate zero-knowledge proofs. These proofs can then be used for trustless verification on the blockchain, ensuring data integrity while maintaining privacy.

Recently, Polygon launched Polygon ID, a zero-knowledge decentralized identity solution. Polygon ID leverages the power of zero-knowledge proofs to allow users to verify their identity without revealing sensitive information. It provides a comprehensive toolset including validator SDK, issuer node, wallet SDK and wallet application, enabling developers to seamlessly integrate decentralized identity solutions into their applications.

in conclusion

All in all, the diversity of areas where ZK has had a positive impact shows the potential of this technology to bring mass adoption to the blockchain industry. In fact, most of these applications—zkML, ZK games, ZK IDs—are still in their infancy, and some of them remain largely in the realm of theory. Still, it’s only a matter of time before we see more activity and products from the zkML, ZK games or ZK ID space. As these areas mature, we expect a vibrant ecosystem of ZK-based applications that will redefine our notions of privacy, security, and verifiability.