We introduce Zero-Knowledge Location Privacy (ZKLP), enabling users to prove to third parties that they are within a specified geographical region while not disclosing their exact location. ZKLP supports varying levels of granularity, allowing for customization depending on the use case. To realize ZKLP, we introduce the first set of Zero-Knowledge Proof (ZKP) circuits that are fully compliant to the IEEE 754 standard for floating-point arithmetic. Our results demonstrate that our floating point circuits amortize efficiently, requiring only 64 constraints per operation for 215single-precision floating-point multiplications. We utilize our floating point implementation to realize the ZKLP paradigm. In comparison to a baseline, we find that our optimized implementation has 15.9× less constraints utilizing single precision floating-point values, and 12.2× less constraints when utilizing double precision floating-point values. We demonstrate the practicability of ZKLP by building a protocol for privacy preserving peer-to-peer proximity testing - Alice can test if she is close to Bob by receiving a single message, without either party revealing any other information about their location. In such a setting, Bob can create a proof of (non-)proximity in 0.26 s, whereas Alice can verify her distance to about 470 peers per second.

Transport Layer Security (TLS) is foundational for safeguarding client-server communication. However, it does not extend integrity guarantees to third-party verification of data authenticity. If a client wants to present data obtained from a server, it cannot convince any other party that the data has not been tampered with. TLS oracles ensure data authenticity beyond the client-server TLS connection, such that clients can obtain data from a server and ensure provenance to any third party, without server-side modifications. Generally, a TLS oracle involves a third party, the verifier, in a TLS session to verify that the data obtained by the client is accurate. Existing protocols for TLS oracles are communication-heavy, as they rely on interactive protocols. We present ORIGO, a TLS oracle with constant communication. Similar to prior work, ORIGO introduces a third party in a TLS session, and provides a protocol to ensure the authenticity of data transmitted in a TLS session, without forfeiting its confidentiality. Compared to prior work, we rely on intricate details specific to TLS 1.3, which allow us to prove correct key derivation, authentication and encryption within a Zero Knowledge Proof (ZKP). This, combined with optimizations for TLS 1.3, leads to an efficient protocol with constant communication in the online phase. Our work reduces online communication by 375× and online runtime by up to 4.6×, compared to prior work.

Web users can gather data from secure endpoints and demonstrate the provenance of sensitive data to any third party by using privacy-preserving TLS oracles. In practice, privacy-preserving TLS oracles remain limited and cannot verify larger, sensitive data sets. In this work, we introduce new optimizations for TLS oracles, which enhance the efficiency of selectively verifying the provenance of confidential web data. The novelty of our work is a construction which secures an honest verifier zero-knowledge proof system in the asymmetric privacy setting while retaining security against malicious adversaries. Concerning TLS 1.3 in the one round-trip time (1-RTT) mode, we propose a new, optimized garble-then-prove paradigm in a security setting with malicious adversaries. Our improvements reach new performance benchmarks and facilitate a practical deployment of privacy-preserving TLS oracles in web browsers.

Latest identity systems rely on public blockchains to enhance user autonomy and reduce tracking from conventional identity providers. At the same time, identity systems integrate novel technologies such as zero-knowledge proofs (ZKPs) to improve data privacy and data compliance. We show that a naive verification of ZKPs at smart contracts enables replay attacks: Attackers can replay ZKPs at arbitrary times without having access to the private inputs that are required for the computation of the ZKP. To solve this problem, we construct a transaction sequence which verifies time-bound and replay-resistant ZKPs at smart contracts. Our construction introduces an additional but constant fee of 0.14${\$}$ per verification of a ZKP on the public blockchain Ethereum. With our new construction, we propose Portal, a novel identity system for decentralized single sign-on.

Modern privacy-enhancing technologies reach new forms of computation and data privacy according to a statement (e.g. private value $\gt \mathbf{100}$). However, beyond the statement expression, the description of a private computation circuit requires knowledge of security algorithms protecting private values. To keep the description of private and compliant computation circuits as close to the statement expression as possible, we introduce a new composable policy language called zkPolicy. Further, we introduce a policy transpiler, called zkGen, to decouple the complexity expressed via zkPolicy from the complexity of the underlying security algorithms. Our results show that, with zkPolicy, the description of compliant data provenance circuits can be reduced from 957 to 22 lines of code. And, with zkGen, we automate the generation and composition of private computation circuits to a minimum effort of configuring a zkPolicy.

Permissionless blockchains promise resilience against censorship by a single entity. This suggests that deterministic rules, not third-party actors, decide whether a transaction is appended to the blockchain. In 2022, the U.S. ØFAC sanctioned a Bitcoin mixer and an Ethereum application, challenging the neutrality of permissionless blockchains.

Society appears to be on the verge of recognizing the need for control over sensitive data in modern web applications. Recently, many systems claim to give control to individuals, promising the preeminent goal of data sovereignty. However, despite recent attention, research and industry efforts are fragmented and lack a holistic system overview. In this paper, we provide the first transecting systematization of data sovereignty by drawing from a dispersed body of knowledge. We clarify the field by identifying its three main areas: (i) decentralized identity, (ii) decentralized access control and (iii) policy-compliant decentralized computation. We find that literature lacks a cohesive set of formal definitions. Each area is considered in isolation, and priorities in industry and academia are not aligned due to a lack of clarity regarding user control. To solve this issue, we propose formal definitions for each sub-area. By highlighting that data sovereignty transcends the domain of decentralized identity, we aim to guide future works to embrace a broader perspective on user control. In each section, we augment our definition with security and privacy properties, discuss the state of the art and proceed to identify open challenges. We conclude by highlighting synergies between areas, emphasizing the real-world benefit obtained by further developing data sovereign systems.

Emerging identity systems in the Web 3.0 achieve a new notion of digital ownership and control. Yet, existing identity ecosystems face bootstrapping issues as trustworthy authorities cannot be represented with adequate privacy. To equip authorities with trustworthy attributes, this work introduces a protocol of domain ownership oracles, where domain owners can prove domain ownership to any third party while remaining anonymous. To prove ownership of an anonymous domain example. com, users convince verifiers of t he f acts that (i) example.com is in control of users and that (ii) example.com belongs to a public anonymity set of domains. Verifiers learn nothing beyond these two facts and cannot determine which user owns which domain. For the first time, o ur work proposes a practical system to attribute anonymous domain owners with credentials of domain ownership where the degree of anonymity depends on the size of a public anonymity set of domains.

Within just four years, the blockchain-based Decentralized Finance (DeFi) ecosystem has accumulated a peak total value locked (TVL) of more than 253 billion USD. This surge in DeFi’s popularity has, unfortunately, been accompanied by many impactful incidents. According to our data, users, liquidity providers, speculators, and protocol operators suffered a total loss of at least 3.24 billion USD from Apr 30, 2018 to Apr 30, 2022. Given the blockchain’s transparency and increasing incident frequency, two questions arise: How can we systematically measure, evaluate, and compare DeFi incidents? How can we learn from past attacks to strengthen DeFi security?In this paper, we introduce a common reference frame to systematically evaluate and compare DeFi incidents, including both attacks and accidents. We investigate 77 academic papers, 30 audit reports, and 181 real-world incidents. Our data reveals several gaps between academia and the practitioners’ community. For example, few academic papers address "price oracle attacks" and "permissonless interactions", while our data suggests that they are the two most frequent incident types (15% and 10.5% correspondingly). We also investigate potential defenses, and find that: (i) 103 (56%) of the attacks are not executed atomically, granting a rescue time frame for defenders; (ii) bytecode similarity analysis can at least detect 31 vulnerable/23 adversarial contracts; and (iii) 33 (15.3%) of the adversaries leak potentially identifiable information by interacting with centralized exchanges.