Understanding Zero-Knowledge Proofs and Their Innovative Role in Blockchain

Innovation & Ideation

Key Insights

• Zero-Knowledge Proofs (ZKPs), a cryptographic method, enhances privacy and security in blockchain transactions without sacrificing transparency.

• Advanced forms of ZKP, like zk-SNARKs and zk-STARKs, have evolved to provide shorter proofs, lower computational requirements, and eliminate the need for a trusted setup.

• ZKPs are revolutionising a range of blockchain applications, from Digital Identity and Traffic Management Systems to Mobile Health, ridesharing, and real estate transactions, by ensuring privacy-centric verification.

• Despite their benefits, ZKPs present challenges, including non-deterministic truthfulness, potential undisclosed secrets, and integrity risks. They also require considerable computational resources and lack user-friendliness for developers.

• Despite these challenges, ZKPs play a crucial role in the ongoing evolution of blockchain technologies, promising a future for more private, secure, and decentralised systems.

Introduction

Blockchain technology, while acclaimed for its decentralisation and transparency, often wrestles with the need for confidentiality and privacy. This is where Zero-Knowledge Proofs come into play. They are a groundbreaking solution reconciling the dichotomy between transparency and privacy on blockchain platforms. In the context of blockchain transactions, ZKPs can verify the validity of transactions without disclosing any of the transaction details, thereby maintaining privacy while still ensuring security [KMS+16]. With the use of ZKPs in the blockchain, it is possible to maintain the immutability and transparency of the blockchain while ensuring the confidentiality of the information [MGGR13].

Fig. 18 Zero-Knowledge Proof Protocol Flow.

Deep Dive: What Are Zero-Knowledge Proofs?

Zero-Knowledge Proof

A ZKP is a cryptographic method that enables one party (the prover) to prove to another party (the verifier) that they possess a specific piece of information, without disclosing the information itself, apart from asserting its truth.

The theoretical concept of Zero-Knowledge Proofs was initially introduced by Goldwasser et al. [GMR19] in their 1985 groundbreaking paper. Their introduction revolutionised the world of cryptography, and they are now an integral part of many privacy-enhancing technologies. As an innovative concept, ZKPs have the potential to significantly enhance confidentiality in blockchain technology, with broad applications ranging from digital identity verification to decentralised finance (DeFi) and private voting systems.

A study by Kosba et al. [KMS+16] illustrated the effective implementation of ZKPs in blockchain technology, using the Zerocash protocol. This innovative protocol allows blockchain users to conduct transactions without disclosing the sender, receiver, or transaction value, thereby ensuring optimal confidentiality.

ZK-SNARKs (Zero-Knowledge Succinct Non-Interactive Argument of Knowledge)

These are compact, quick to verify cryptographic proofs that allow one party to prove they know specific information without revealing that information. The downside is they require a “trusted setup,” where a secret parameter must be generated and then destroyed.

ZK-STARKs (Zero-Knowledge Scalable Transparent Arguments of Knowledge)

These are similar to ZK-SNARKs, but they don’t require a trusted setup, making them more secure. They also remain efficient even as the amount of information being proved increases, and they’re resistant to quantum computing attacks. However, they generate larger proof sizes compared to ZK-SNARKs.

The development and refinement of ZKPs have led to advanced cryptographic protocols like zk-SNARKs and zk-STARKs. Ben-Sasson et al. [BSCTV14] introduced zk-SNARKs, an upgraded version of ZKPs, which offer shorter proofs and reduced computational requirements. To overcome the limitations of zk-SNARKs, particularly the ‘trusted setup’ condition, zk-STARKs were proposed, which offer similar benefits without the need for a trusted setup.

The Innovative Role of ZKPs in Blockchain

The introduction of ZKPs in blockchain technologies has enabled a new layer of confidentiality. Specifically, they can validate the truth of a transaction without revealing details about the transaction itself, which opens up new avenues for privacy-preserving applications on blockchain platforms [KMS+16].

Digital Identity Management Systems

Traditional centralised Digital Identity Management Systems (DIMS) are vulnerable to various threats, such as fragmented identity, single point of failure, internal attacks, and privacy leaks. However, the introduction of blockchain technology can mitigate these issues by eliminating the need for a centralised third party. Yet, the inherent transparency of the blockchain also poses privacy challenges due to its open nature.

To address these issues, smart contracts and zero-knowledge proof (ZKP) algorithms can be used to refine the current identity claim model on the blockchain. This enhances the unlinkability of identities and prevents the exposure of attribute ownership, thereby improving user privacy.

The solution also introduces a challenge-response protocol that allows users to selectively reveal attribute ownership to service providers. Notably, during user access to services, authentication is carried out via zero-knowledge proof rather than Identity Providers (IdPs). This means the authentication details are only visible to the service provider, which further safeguards user behaviour privacy [YL20].

Traffic Management Systems

Modern traffic systems use a wealth of vehicular data for real-time decision-making, but integrating real-time data from connected vehicles poses data security and privacy challenges. While blockchain has offered innovative solutions, its transparency can compromise privacy.

The non-interactive zero-knowledge range proof (ZKRP) protocol can be used to address privacy concerns in traffic management systems, where sensitive data is often exposed due to blockchain’s transparency. This protocol verifies the correctness of a piece of information without revealing any extra details beyond the verification itself. It is a critical component of the proposed decentralised, location-aware architecture designed for maintaining data integrity and privacy in blockchain-based traffic management systems. By leveraging the capabilities of the Hyperledger Fabric platform and the Hyperledger Ursa cryptographic library, this innovative approach has demonstrated its effectiveness and feasibility for real-time traffic management, all while fulfilling necessary data privacy requirements [LGNS20].

Privacy in Mobile Health Systems

The surge of compact mobile devices with wireless connectivity and integrated biosensors has transformed healthcare systems. These wearable devices, part of mobile health (mHealth), regularly collect health data, enabling remote patient monitoring and healthcare services. However, mHealth introduces substantial privacy risks, primarily due to its smartphone-based management system. Specifically, the communication between the monitoring devices and the smartphone, typically via Bluetooth, presents security challenges. Devices are usually paired with a smartphone but aren’t necessarily linked exclusively to a specific mHealth app, leaving room for potential data breaches or illegitimate data injection.

To mitigate these risks, Non-Interactive Zero-Knowledge Proof can be used as part of a lightweight authentication scheme. This protocol is specifically designed to operate efficiently even on mHealth devices that have limited resources. By implementing this approach, we can ensure that only authorised devices have the ability to interact with the official mHealth application, which significantly strengthens the security and privacy protections of mHealth systems [TDNHDS20].

Identity Verification for Safe Ridesharing

Ridesharing offers several advantages, like reducing traffic congestion and environmental impact. However, the safety and privacy of both riders and drivers is a crucial concern, highlighting the need for a system that can verify identities while preserving privacy among untrusted parties.

In response to this need, a novel system is proposed, integrating zero-knowledge proof (ZKP) and blockchain technology for use in ridesharing applications. This system employs a permissioned blockchain network to verify a driver’s identity using ZKP while also acting as a secure ledger to record ride logs and ZKP records. A protocol is developed to allow user verification without the need to share any private information. The system has been prototyped on the Hyperledger Fabric platform, utilising the Hyperledger Ursa cryptography library, ensuring the secure and private verification of identities in ridesharing applications [LMGN20].

Real Estate Contracts

Given the high stakes involved in real estate contracts, the prevention of forgery and duplication is crucial, especially in the online space. Blockchain technology is emerging as a solution, improving the reliability of such contracts. However, as online real estate transactions using blockchain increase, scalability becomes an issue.

This is where the zero-knowledge proof algorithm comes into play. A novel Ethereum-based online real estate contract system that leverages this algorithm to enhance scalability. The system effectively manages contracts online and detects potential contract forgery via the blockchain. Importantly, the use of the zero-knowledge proof algorithm allows for scalability while preserving security and privacy. This enables the system to prevent fraudulent activities throughout the entire contract process, from initiation to termination. The incorporation of this algorithm thus strengthens the overall reliability and security of real estate transactions conducted online [JA21].

Challenges and Limitations

Zero-knowledge proof, despite its innovative approach, grapples with some limitations and vulnerabilities. Its non-deterministic characteristic means that there isn’t an absolute guarantee that the generated values are truthful, but rather, they carry a high probability of being accurate. The technology’s verification process, while preserving confidentiality, can also result in the underlying secret remaining undisclosed perpetually. Furthermore, if an untrustworthy party is involved in the process, there’s a risk of integrity compromise, as they could manipulate the interactions to yield misleading outcomes [Faw23].

Requires a large amount of computation

Zero-knowledge Proof (ZKP) protocols, comprising intricate algorithms, necessitate an extensive amount of computational resources for their operation and execution. This considerable demand on processing power may pose challenges for common computers involved in the verification process [Bho22].

Not developer friendly

ZKP doesn’t offer a user-friendly experience, particularly for developers. For instance, Zk Rollup, a Layer 2 solution that employs ZKP to enhance the scalability of Blockchain, is presently restricted to basic payment applications. The technology is yet to support aggregation, posing significant limitations for its users [Bho22].

Conclusion

As blockchain technologies continue to evolve, the role of Zero-Knowledge Proofs in shaping the future of blockchain applications is undeniably significant. By enabling verification without compromising confidentiality, ZKPs open the door to a vast array of innovative applications in various industries. From digital identity and cybersecurity to decentralised finance and voting systems, the potential for ZKPs to promote a more private, secure, and decentralised future is promising.

Ali Kathia

August 2023

References

BSCTV14

Eli Ben-Sasson, Alessandro Chiesa, Eran Tromer, and Madars Virza. Succinct non-interactive zero knowledge for a von neumann architecture. In 23rd $\$USENIX$\$ Security Symposium ($\$USENIX$\$ Security 14), 781–796. 2014.

Bho22(1,2)

BhoNetwork. What is zero-knowledge proof (zkp)? details about zkp. BHO NETWORK, 2022. URL: https://bho.network/en/what-is-zero-knowledge-proof#h3-21.

Faw23

John Fawole. Zero-knowledge proof – how it works. hacken.io, 2023. URL: https://hacken.io/discover/zero-knowledge-proof/#Advantages_and_Disadvantages_of_Zero-Knowledge_Proof.

GMR19

Shafi Goldwasser, Silvio Micali, and Chales Rackoff. The knowledge complexity of interactive proof-systems. In Providing Sound Foundations for Cryptography: On the Work of Shafi Goldwasser and Silvio Micali, pages 203–225. 2019.

JA21

SoonHyeong Jeong and Byeongtae Ahn. Implementation of real estate contract system using zero knowledge proof algorithm based blockchain. The Journal of Supercomputing, 77(10):11881–11893, 2021.

KMS+16(1,2,3)

Ahmed Kosba, Andrew Miller, Elaine Shi, Zikai Wen, and Charalampos Papamanthou. Hawk: the blockchain model of cryptography and privacy-preserving smart contracts. In 2016 IEEE symposium on security and privacy (SP), 839–858. IEEE, 2016.

LGNS20

Wanxin Li, Hao Guo, Mark Nejad, and Chien-Chung Shen. Privacy-preserving traffic management: a blockchain and zero-knowledge proof inspired approach. IEEE access, 8:181733–181743, 2020.

LMGN20

Wanxin Li, Collin Meese, Hao Guo, and Mark Nejad. Blockchain-enabled identity verification for safe ridesharing leveraging zero-knowledge proof. In 2020 3rd International Conference on Hot Information-Centric Networking (HotICN), 18–24. IEEE, 2020.

MGGR13

Ian Miers, Christina Garman, Matthew Green, and Aviel D Rubin. Zerocoin: anonymous distributed e-cash from bitcoin. In 2013 IEEE Symposium on Security and Privacy, 397–411. IEEE, 2013.

TDNHDS20

Antonio Emerson Barros Tomaz, Jose Claudio Do Nascimento, Abdelhakim Senhaji Hafid, and Jose Neuman De Souza. Preserving privacy in mobile health systems using non-interactive zero-knowledge proof and blockchain. IEEE access, 8:204441–204458, 2020.

YL20

Xiaohui Yang and Wenjie Li. A zero-knowledge-proof-based digital identity management scheme in blockchain. Computers & Security, 99:102050, 2020.