Related papers: zkFi: Privacy-Preserving and Regulation Compliant …
Privacy concerns in machine learning systems have grown significantly with the increasing reliance on sensitive user data for training large-scale models. This paper introduces a novel framework combining Probably Approximately Correct…
Ethereum's scalability limitations pose significant challenges for the adoption of decentralized applications (dApps). Zero-Knowledge Rollups (ZK Rollups) present a promising solution, bundling transactions off-chain and submitting validity…
While the amount of data produced and accumulated continues to advance at unprecedented rates, protection and concealment of data increase its prominence as a field of scientific study that requires more action. It is essential to protect…
The modern integrated circuit ecosystem is increasingly reliant on third-party intellectual property integration, which introduces security risks, including hardware Trojans and security vulnerabilities. Addressing the resulting trust…
This paper presents a framework for securing blockchain-based IoT systems by integrating Physical Unclonable Functions (PUFs) and Zero-Knowledge Proofs (ZKPs) within a Hyperledger Fabric environment. The proposed framework leverages PUFs…
A Zero-Knowledge Protocol (ZKP) allows one party to convince another party of a fact without disclosing any extra knowledge except the validity of the fact. For example, it could be used to allow a customer to prove their identity to a…
Federated Learning (FL) has emerged as a promising paradigm in distributed machine learning, enabling collaborative model training while preserving data privacy. However, despite its many advantages, FL still contends with significant…
Federated Learning (FL) enables collaborative model training on decentralized data without exposing raw data. However, the evaluation phase in FL may leak sensitive information through shared performance metrics. In this paper, we propose a…
Since the concern of privacy leakage extremely discourages user participation in sharing data, federated learning has gradually become a promising technique for both academia and industry for achieving collaborative learning without leaking…
Intuitively there is a drastic distinction between the pure decentralized block-chain systems like Defis and those that only utilize block-chain as an enhancing technology but remain centralized with real-world business model and…
Zero-knowledge proofs have always provided a clear solution when it comes to conveying information from a prover to a verifier or vice versa without revealing essential information about the process. Advancements in zero-knowledge have…
Zero-knowledge proofs (ZKPs) are computationally demanding to generate. Their importance for applications like ZK-Rollups has prompted some to outsource ZKP generation to a market of specialized provers. However, existing market designs…
In last years, there has been an increasing effort to leverage Distributed Ledger Technology (DLT), including blockchain. One of the main topics of interest, given its importance, is the research and development of privacy mechanisms, as…
Machine learning is increasingly deployed through outsourced and cloud-based pipelines, which improve accessibility but also raise concerns about computational integrity, data privacy, and model confidentiality. Zero-knowledge proofs (ZKPs)…
How someone can get health insurance without sharing his health information? How you can get a loan without disclosing your credit score? There is a method to certify certain attributes of various data, either this is health metrics or…
Zero-Knowledge Proofs (ZKPs) are rapidly gaining importance in privacy-preserving and verifiable computing. ZKPs enable a proving party to prove the truth of a statement to a verifying party without revealing anything else. ZKPs have…
Recent work introduces zkay, a system for specifying and enforcing data privacy in smart contracts. While the original prototype implementation of zkay (v0.1) demonstrates the feasibility of the approach, its proof-of-concept implementation…
Many companies use identity information for different goals. There are a lot of marketplaces for identity information. These markets have some practical issues such as privacy, mutual trust and fairing exchange. The management of identity…
Zero-Knowledge Proofs (ZKPs) have emerged as a powerful tool for secure and privacy-preserving computation. ZKPs enable one party to convince another of a statement's validity without revealing anything else. This capability has profound…
NuLink provides privacy-preserving technology for decentralized applications via APIs. Users can securely store its valuable data, trade with others and so on. To ensure the privacy and security of service provided by NuLink,…