Computational Intelligence and Machine Learning
Improving Privacy with Zero Knowledge Proofs
Authors: Subhranil Das, Rashmi Kumari, Raghwendra Kishore Singh, Dev Rishi and Vansh Gupta
Publishing Date: 23-04-2025
ISBN: 978-81-975670-5-6
Abstract
Zero Knowledge Proofs (ZKPs) have emerged as transformative cryptographic primitives, enabling a wide variety of modern privacy-preserving applications across various domains. This paper presents substantial advancements in contemporary ZKPs, exploring the latest trends in ZKP schemes, novel applications, and scalable ZKP-based systems. We provide an in-depth analysis of state-of-the-art ZKP structures, including zk-SNARKs, zk-STARKs, and the more recent zk-Rollup technologies. We examine the unique properties and use cases of these techniques, highlighting their potential to enhance privacy, security, and trust in digital systems. Our research into zk-Rollups demonstrates significant improvements in transaction throughput and gas efficiency, paving the way for the extensive deployment of modern privacy-preserving solutions. Furthermore, we showcase several innovative applications of ZKPs, such as privacy-preserving decentralized finance (DeFi) protocols, anonymous credentials, and secure multi-party computation. These use cases illustrate the transformative potential of advanced ZKPs to improve privacy and security across a range of digital domains. To foster wider adoption of modern ZKPs, we have developed and opensourced a collection of advanced tools and libraries that simplify the implementation of ZKP-based solutions. We also offer practical guidance and best practices for developers and researchers working in this field, aiming to accelerate the development and real-world impact of modern zero-knowledge proof systems.
Keywords
Zero Knowledge pro brand news, zk-SNARKs, zk-STARKs, decentralized finance.
Cite as
Subhranil Das, Rashmi Kumari, Raghwendra Kishore Singh, Dev Rishi and Vansh Gupta, "Improving Privacy with Zero Knowledge Proofs", In: Sandeep Kumar and Kavita Sharma (eds), Computational Intelligence and Machine Learning, SCRS, India, 2025, pp. 1-10. https://doi.org/10.56155/978-81-975670-5-6-1