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Publications

2025

Approaches to Conflict-free Replicated Data Types

Authors
Almeida, PS;

Publication
ACM COMPUTING SURVEYS

Abstract
Conflict-free Replicated Data Types (CRDTs) allow optimistic replication in a principled way. Different replicas can proceed independently, being available even under network partitions and always converging deterministically: Replicas that have received the same updates will have equivalent state, even if received in different orders. After a historical tour of the evolution from sequential data types to CRDTs, we present in detail the two main approaches to CRDTs, operation-based and state-based, including two important variations, the pure operation-based and the delta-state based. Intended for prospective CRDT researchers and designers, this article provides solid coverage of the essential concepts, clarifying some misconceptions that frequently occur, but also presents some novel insights gained from considerable experience in designing both specific CRDTs and approaches to CRDTs.

2025

GANs in the Panorama of Synthetic Data Generation Methods

Authors
Vaz, B; Figueira, A;

Publication
ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS

Abstract
This article focuses on the creation and evaluation of synthetic data to address the challenges of imbalanced datasets in machine learning (ML) applications, using fake news detection as a case study. We conducted a thorough literature review on generative adversarial networks (GANs) for tabular data, synthetic data generation methods, and synthetic data quality assessment. By augmenting a public news dataset with synthetic data generated by different GAN architectures, we demonstrate the potential of synthetic data to improve ML models' performance in fake news detection. Our results show a significant improvement in classification performance, especially in the underrepresented class. We also modify and extend a data usage approach to evaluate the quality of synthetic data and investigate the relationship between synthetic data quality and data augmentation performance in classification tasks. We found a positive correlation between synthetic data quality and performance in the underrepresented class, highlighting the importance of high-quality synthetic data for effective data augmentation.

2025

Logic and Calculi for All on the occasion of Luis Barbosa's 60th birthday

Authors
Madeira, A; Oliveira, JN; Proença, J; Neves, R;

Publication
JOURNAL OF LOGICAL AND ALGEBRAIC METHODS IN PROGRAMMING

Abstract
[No abstract available]

2025

A Tight Security Proof for SPHINCS+, Formally Verified

Authors
Barbosa, M; Dupressoir, F; Hülsing, A; Meijers, M; Strub, P;

Publication
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Abstract
SPHINCS+ is a post-quantum signature scheme that, at the time of writing, is being standardized as SLH-DSA. It is the most conservative option for post-quantum signatures, but the original tight proofs of security were flawed — as reported by Kudinov, Kiktenko and Fedorov in 2020. In this work, we formally prove a tight security bound for SPHINCS+ using the EasyCrypt proof assistant, establishing greater confidence in the general security of the scheme and that of the parameter sets considered for standardization. To this end, we reconstruct the tight security proof presented by Hülsing and Kudinov (in 2022) in a modular way. A small but important part of this effort involves a complex argument relating four different games at once, of a form not yet formalized in EasyCrypt (to the best of our knowledge). We describe our approach to overcoming this major challenge, and develop a general formal verification technique aimed at this type of reasoning. Enhancing the set of reusable EasyCrypt  artifacts previously produced in the formal verification of stateful hash-based cryptographic constructions, we (1) improve and extend the existing libraries for hash functions and (2) develop new libraries for fundamental concepts related to hash-based cryptographic constructions, including Merkle trees. These enhancements, along with the formal verification technique we develop, further ease future formal verification endeavors in EasyCrypt, especially those concerning hash-based cryptographic constructions. © International Association for Cryptologic Research 2025.

2025

Leakage-Free Probabilistic Jasmin Programs

Authors
Almeida, JB; Firsov, D; Oliveira, T; Unruh, D;

Publication
Proceedings of the 14th ACM SIGPLAN International Conference on Certified Programs and Proofs, CPP 2025, Denver, CO, USA, January 20-21, 2025

Abstract
This paper presents a semantic characterization of leakage-freeness through timing side-channels for Jasmin programs. Our characterization covers probabilistic Jasmin programs that are not constant-time. In addition, we provide a characterization in terms of probabilistic relational Hoare logic and prove the equivalence between both definitions. We also prove that our new characterizations are compositional and relate our new definitions to existing ones from prior work, which could only be applied to deterministic programs. To provide practical evidence, we use the Jasmin framework to develop a rejection sampling algorithm and provide an EasyCrypt proof that ensures the algorithm’s implementation is leakage-free while not being constant-time. © 2025 Copyright held by the owner/author(s).

2025

On Bridging Prolog and Python to Enhance an Inductive Logic Programming System

Authors
Costa, VS; Areias, M;

Publication
Lecture Notes in Computer Science - Practical Aspects of Declarative Languages

Abstract

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