arXiv subjects

Stephan Krenn

Publications and source records attributed to Stephan Krenn.

11 recordsLinked to original sources

arXiv2026

bpK#: Delegatable Pseudonyms And Their Applications to National eID Systems

Electronic identities (eIDs) are crucial in an increasingly digitalized environment. Pseudonyms, as offered by Austria's governmental sector-specific personal identifiers (bPks), can significantly improve privacy by ensuring that personal data is not universally traceable across public services and private companies. However, the current architecture comes with several challenges regarding availability, privacy, and authenticity, due to a fully centralized design. This paper proposes bPk#, a distributed architecture to address these issues, reducing reliance on the central authority, while still providing all functional requirements to the existing bPk system. In particular, users are delegated the rights to compute their own pseudonyms, thereby minimizing metadata revealed to the central authority, while (subsets of) service providers may receive the right to compute pseudonyms only within their own domain, thereby reducing the availability needs of the central authority. To the best of our knowledge, we provide the first formal framework for such delegatable pseudonym systems, together with a generic construction for which we provide formal security proofs. Furthermore, we propose a concrete instantiation of our construction, together with a reference implementation demonstrating the practical efficiency.

cs.CR↗

arXiv2026

Topology-Hiding Path Validation for Large-Scale Quantum Key Distribution Networks

Secure long-distance communication in quantum key distribution (QKD) networks depends on trusted repeater nodes along the entire transmission path. Consequently, these nodes will be subject to strict auditing and certification in future large-scale QKD deployments. However, trust must also extend to the network operator, who is responsible for fulfilling contractual obligations -- such as ensuring certified devices are used and transmission paths remain disjoint where required. In this work, we present a path validation protocol specifically designed for QKD networks. It enables the receiver to verify compliance with agreed-upon policies. At the same time, the protocol preserves the operator's confidentiality by ensuring that no sensitive information about the network topology is revealed to users. We provide a formal model and a provably secure generic construction of the protocol, along with a concrete instantiation. For long-distance communication involving 100 nodes, the protocol has a computational cost of 1-2.5s depending on the machine, and a communication overhead of less than 70kB - demonstrating the efficiency of our approach.

quant-ph↗

arXiv2026

Topology-Hiding Connectivity-Assurance for QKD Inter-Networking

While QKD ensures information-theoretic security at the link level, real-world deployments depend on trusted repeaters, creating potential vulnerabilities. In this paper, we thus introduce a topology-hiding connectivity assurance protocol to enhance trust in quantum key distribution (QKD) network infrastructures. Our protocol allows network providers to jointly prove the existence of a secure connection between endpoints without revealing internal topology details. By extending graph-signature techniques to support multi-graphs and hidden endpoints, we enable zero-knowledge proofs of connectivity that ensure both soundness and topology hiding. We further discuss how our approach can certify, e.g., multiple disjoint paths, supporting multi-path QKD scenarios. This work bridges cryptographic assurance methods with the operational requirements of QKD networks, promoting verifiable and privacy-preserving inter-network connectivity.

cs.CR↗

arXiv2025

QoeSiGN: Towards Qualified Collaborative eSignatures

eSignatures ensure data's authenticity, non-repudiation, and integrity. EU's eIDAS regulation specifies, e.g., advanced and qualified (QES) eSignatures. While eSignatures' concrete legal effects depend on the individual case, QESs constitute the highest level of technical protection and authenticity under eIDAS. QESs are based on a qualified certificate issued by a qualified trust service provider (QTSP). Despite legal requirements, technically, a QTSP represents a single point of failure. Contrary, privacy-preserving collaborative computations (P2C2s) have become increasingly practical in recent years; yet lacking an extensive investigation on potential integrations in the QES landscape. We perform a threat analysis on the QES-creation process of Austria's national eID, using STRIDE and a DREAD-like model to extract requirement challenges (RCs) primarily related to: (1) Distributed Service Robustness, (2) Agile Crypto Deployment, and (3) Active User Involvement. To address these RCs, we present QoeSiGN, utilizing novel P2C2 technologies. While currently no P2C2 addresses all RCs, legal aspects, and practical efficiency simultaneously, QoeSiGN gives instantiation possibilities for different needs. For instance, "Multi-Party HSMs" for distributed hardware-secured computations; or secure multi-party computation (software) for highest crypto agility and user involvement, where the user participates in the QES computation. Deployment-wise, QTSPs would need to adapt the signing process and setup trusted communication channels. Legal-wise, QoeSiGN's implementation appears permissible, needing further analysis for realization. Technically, QoeSiGN addresses some regulation requirements better than the current solution, such as "sole control" or crypto agility. Our identified threats and extracted requirements can be transferred to the general QES ecosystem.

cs.CR↗

arXiv2024

Secure Computation and Trustless Data Intermediaries in Data Spaces

This paper explores the integration of advanced cryptographic techniques for secure computation in data spaces to enable secure and trusted data sharing, which is essential for the evolving data economy. In addition, the paper examines the role of data intermediaries, as outlined in the EU Data Governance Act, in data spaces and specifically introduces the idea of trustless intermediaries that do not have access to their users' data. Therefore, we exploit the introduced secure computation methods, i.e. Secure Multi-Party Computation (MPC) and Fully Homomorphic Encryption (FHE), and discuss the security benefits. Overall, we identify and address key challenges for integration, focusing on areas such as identity management, policy enforcement, node selection, and access control, and present solutions through real-world use cases, including air traffic management, manufacturing, and secondary data use. Furthermore, through the analysis of practical applications, this work proposes a comprehensive framework for the implementation and standardization of secure computing technologies in dynamic, trustless data environments, paving the way for future research and development of a secure and interoperable data ecosystem.

cs.CR↗

arXiv2024

Protecting Privacy in Federated Time Series Analysis: A Pragmatic Technology Review for Application Developers

The federated analysis of sensitive time series has huge potential in various domains, such as healthcare or manufacturing. Yet, to fully unlock this potential, requirements imposed by various stakeholders must be fulfilled, regarding, e.g., efficiency or trust assumptions. While many of these requirements can be addressed by deploying advanced secure computation paradigms such as fully homomorphic encryption, certain aspects require an integration with additional privacy-preserving technologies. In this work, we perform a qualitative requirements elicitation based on selected real-world use cases. We match the derived requirements categories against the features and guarantees provided by available technologies. For each technology, we additionally perform a maturity assessment, including the state of standardization and availability on the market. Furthermore, we provide a decision tree supporting application developers in identifying the most promising technologies available matching their needs. Finally, existing gaps are identified, highlighting research potential to advance the field.

cs.CR↗

arXiv2022

On the Security of Offloading Post-Processing for Quantum Key Distribution

Quantum key distribution (QKD) has been researched for almost four decades and is currently making its way to commercial applications. However, deployment of the technology at scale is challenging, because of the very particular nature of QKD and its physical limitations. Among others, QKD is computationally intensive in the post-processing phase and devices are therefore complex and power hungry, which leads to problems in certain application scenarios. In this work we study the possibility to offload computationally intensive parts in the QKD post-processing stack in a secure way to untrusted hardware. We show how error correction can be securely offloaded for discrete-variable QKD to a single untrusted server and that the same method cannot be used for long distance continuous-variable QKD. Furthermore, we analyze possibilities for multi-server protocols to be used for error correction and privacy amplification. Even in cases where it is not possible to offload to an external server, being able to delegate computation to untrusted hardware components on the device could improve the cost and certification effort for device manufacturers.

quant-ph↗

arXiv2022

Single-Use Delegatable Signatures Based on Smart Contracts

Delegation of cryptographic signing rights has found many application in the literature and the real world. However, despite very advanced functionalities and specific use cases, existing solutions share the natural limitation that the number of usages of these signing rights cannot be efficiently limited, but users can at most be disincentivized to abuse their rights. In this paper, we suggest a solution to this problem based on blockchains. We let a user define a smart contract defining delegated signing rights, which needs to be triggered to successfully sign a message. By leveraging the immutability of the blockchain, our construction can now guarantee that a user-defined threshold of signature invocations cannot be exceeded, thereby circumventing the need for dedicated hardware or similar assistance in existing constructions for one-time programs. We discuss different constructions supporting different features, and provide concrete implementations in the Solidity language of the Ethereum blockchain, proving the real-world efficiency and feasibility of our construction.

cs.CR↗

arXiv2022

A Verifiable Multiparty Computation Solver for the Assignment Problem and Applications to Air Traffic Management

The assignment problem is an essential problem in many application fields and frequently used to optimize resource usage. The problem is well understood and various efficient algorithms exist to solve the problem. However, it was unclear what practical performance could be achieved for privacy preserving implementations based on multiparty computation (MPC) by leveraging more efficient solution strategies than MPC based simplex solvers for linear programs. We solve this question by implementing and comparing different optimized MPC algorithms to solve the assignment problem for reasonable problem sizes. Our empirical approach revealed various insights to MPC based optimization and we measured a significant (50x) speedup compared to the known simplex based approach. Furthermore, we also study the overhead introduced by making the results publicly verifiable by means of non-interactive zero-knowledge proofs. By leveraging modern proof systems we also achieve significant speedup for proof and verification times compared to the previously proposed approaches as well as compact proof sizes.

cs.CR↗

arXiv2021

Privacy-preserving Analytics for Data Markets using MPC

Data markets have the potential to foster new data-driven applications and help growing data-driven businesses. When building and deploying such markets in practice, regulations such as the European Union's General Data Protection Regulation (GDPR) impose constraints and restrictions on these markets especially when dealing with personal or privacy-sensitive data. In this paper, we present a candidate architecture for a privacy-preserving personal data market, relying on cryptographic primitives such as multi-party computation (MPC) capable of performing privacy-preserving computations on the data. Besides specifying the architecture of such a data market, we also present a privacy-risk analysis of the market following the LINDDUN methodology.

cs.CR↗

arXiv2020

Towards Privacy in Geographic Message Dissemination for Connected Vehicles

With geographic message dissemination, connected vehicles can be served with traffic information in their proximity, thereby positively impacting road safety, traffic management, or routing. Since such messages are typically relevant in a small geographic area, servers only distribute messages to affected vehicles for efficiency reasons. One main challenge is to maintain scalability of the server infrastructure when collecting location updates from vehicles and determining the relevant group of vehicles when messages are distributed to a geographic relevance area, while at the same time respecting the individual user's privacy in accordance with legal regulations. In this paper, we present a framework for geographic message dissemination following the privacy-by-design and privacy-by-default principles, without having to accept efficiency drawbacks compared to conventional server-client based approaches.

cs.CR↗