arXiv subjects

Thomas Attema

Publications and source records attributed to Thomas Attema.

3 recordsLinked to original sources

arXiv2025

Post-Quantum Cryptography in the 5G Core

In this work, the conventional cryptographic algorithms used in the 5G Core are replaced with post-quantum alternatives and the practical impact of this transition is evaluated. Using a simulation environment, we model the registration and deregistration of varying numbers of user equipments (UEs) and measure the resulting effects on bandwidth consumption and latency. Our results show that the deployment of post-quantum cryptographic algorithms has a measurable effect on performance, but that this effect is small, and perhaps more crucially, that the extra overhead needed in terms of computation and bandwidth does not have any substantial impact on the usability of the network and the efficiency of its network functions. Overall the experimental results in this work corroborate earlier research: the 5G Core is technically able to support post-quantum cryptography without any inherent issues connected to the increased computational overhead or larger message size.

cs.CR↗

arXiv2020

Optimizing the Decoy-State BB84 QKD Protocol Parameters

The performance of a QKD implementation is determined by the tightness of the underlying security analysis. In particular, the security analyses determines the key-rate, i.e., the amount of cryptographic key material that can be distributed per time unit. Nowadays, the security analyses of various QKD protocols are well understood. It is known that optimal protocol parameters, such as the number of decoy states and their intensities, can be found by solving a nonlinear optimization problem. The complexity of this optimization problem is typically handled by making an number of heuristic assumptions. For instance, the number of decoy states is restricted to only one or two, with one of the decoy intensities set to a fixed value, and vacuum states are ignored as they are assumed to contribute only marginally to the secure key-rate. These assumptions simplify the optimization problem and reduce the size of search space significantly. However, they also cause the security analysis to be non-tight, and thereby result in sub-optimal performance. In this work, we follow a more rigorous approach using both linear and non-linear programs describing the optimization problem. Our approach, focusing on the Decoy-State BB84 protocol, allows heuristic assumptions to be omitted, and therefore results in a tighter security analysis with better protocol parameters. We show an improved performance for the Decoy-State BB84 QKD protocol, demonstrating that the heuristic assumptions typically made are too restrictive. Moreover, our improved optimization frameworks shows that the complexity of the performance optimization problem can also be handled without making heuristic assumptions, even with limited computational resources available.

quant-ph↗

arXiv2018

A New Approach to Privacy-Preserving Clinical Decision Support Systems

Background: Clinical decision support systems (CDSS) are a category of health information technologies that can assist clinicians to choose optimal treatments. These support systems are based on clinical trials and expert knowledge; however, the amount of data available to these systems is limited. For this reason, CDSSs could be significantly improved by using the knowledge obtained by treating patients. This knowledge is mainly contained in patient records, whose usage is restricted due to privacy and confidentiality constraints. Methods: A treatment effectiveness measure, containing valuable information for treatment prescription, was defined and a method to extract this measure from patient records was developed. This method uses an advanced cryptographic technology, known as secure Multiparty Computation (henceforth referred to as MPC), to preserve the privacy of the patient records and the confidentiality of the clinicians' decisions. Results: Our solution enables to compute the effectiveness measure of a treatment based on patient records, while preserving privacy. Moreover, clinicians are not burdened with the computational and communication costs introduced by the privacy-preserving techniques that are used. Our system is able to compute the effectiveness of 100 treatments for a specific patient in less than 24 minutes, querying a database containing 20,000 patient records. Conclusion: This paper presents a novel and efficient clinical decision support system, that harnesses the potential and insights acquired from treatment data, while preserving the privacy of patient records and the confidentiality of clinician decisions.

cs.CR↗