Related papers: zkay v0.2: Practical Data Privacy for Smart Contra…
Federated learning (FL) enables collaborative model training while preserving data privacy, yet both centralized and decentralized approaches face challenges in scalability, security, and update validation. We propose ZK-HybridFL, a secure…
Zero-knowledge proofs (ZKPs) are an emerging technology that has become the solution to efficiently provide security and privacy along with the transparency requirement of blockchains. ZKPs are usually expressed by means of arithmetic…
Regulations for privacy protection aim to protect individuals from the unauthorized storage, processing, and transfer of their personal data but oftentimes fail in providing helpful support for understanding these regulations. To better…
Smart contracts are computer programs running on blockchains to implement Decentralized Applications. The absence of contract specifications hinders routine tasks, such as contract understanding and testing. In this work, we propose a…
Evaluating the usefulness of data before purchase is essential when obtaining data for high-quality machine learning models, yet both model builders and data providers are often unwilling to reveal their proprietary assets. We present…
We describe the verification of an existing smart contract for a simple casino application, using the Whiley specification and programming language, with a fully automated verification engine based on Boogie and Z3. After finding and fixing…
Most of the smart applications, such as smart energy metering devices, demand strong privacy preservation to strengthen data privacy. However, it is difficult to protect the privacy of the smart device data, especially on the client side.…
Smart contracts are blockchain programs that often handle valuable assets. Writing secure smart contracts is far from trivial, and any vulnerability may lead to significant financial losses. To support developers in identifying 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…
Privacy is one of the essential pillars for the widespread adoption of blockchains, but public blockchains are transparent by nature. Modern analytics techniques can easily subdue the pseudonymity feature of a blockchain user. Some…
Recently, decentralised (on-blockchain) platforms have emerged to complement centralised (off-blockchain) platforms for the implementation of automated, digital (smart) contracts. However, neither alternative can individually satisfy the…
Blockchain offers traceability and transparency to supply chain event data and hence can help overcome many challenges in supply chain management such as: data integrity, provenance and traceability. However, data privacy concerns such as…
This paper explores how zero-knowledge proofs can enhance Bitcoin's functionality and privacy. First, we consider Proof-of-Reserve schemes: by using zk-STARKs, a custodian can prove its Bitcoin holdings are more than a predefined threshold…
Smart contracts on a blockchain behave precisely as specified by their code. A vulnerability in this code can lead to unexpected behaviour, which is hard to fix because a blockchain does not allow to change smart contract code after its…
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…
Authentication, authorization, and trust verification are central parts of an access control system. The conditions for granting access in such a system are collected in access policies. Since access conditions are often complex, dedicated…
The immutable nature of blockchain technology, while revolutionary, introduces significant security challenges, particularly in smart contracts. These security issues can lead to substantial financial losses. Current tools and approaches…
Machine learning models are increasingly used in societal applications, yet legal and privacy concerns demand that they very often be kept confidential. Consequently, there is a growing distrust about the fairness properties of these models…
We present STAMP (Selective Task-Aware Mechanism for Text Privacy), a new framework for task-aware text privatization that achieves an improved privacy-utility trade-off. STAMP selectively allocates privacy budgets across tokens by jointly…
The ever increasing complexity of hardware platforms poses a challenge to systems programmers. Correctly programming a multitude of components, providing functionality and security, is difficult: semantics of individual units are described…