Related papers: TELSAFE: Security Gap Quantitative Risk Assessment…
The emergence of Cryptographically Relevant Quantum Computers (CRQCs) presents a critical threat to classical cryptographic systems, particularly widely adopted protocols such as RSA, Diffie-Hellman (DH), and Elliptic Curve Cryptography…
Clinical LLMs are often scaled by increasing model size, context length, retrieval complexity, or inference-time compute, with the implicit expectation that higher accuracy implies safer behavior. This assumption is incomplete in medicine,…
The advent of Federated Learning (FL) as a distributed machine learning paradigm has introduced new cybersecurity challenges, notably adversarial attacks that threaten model integrity and participant privacy. This study proposes an…
Secure aggregation enables a group of mutually distrustful parties, each holding private inputs, to collaboratively compute an aggregate value while preserving the privacy of their individual inputs. However, a major challenge in adopting…
Risk matrices are widely used across a range of fields and have found increasing utility in warning decision practices globally. However, their application in this context presents challenges, which range from potentially perverse warning…
Advancements in quantum computing pose a significant threat to most of the cryptography currently deployed. Fortunately, cryptographic building blocks to mitigate the threat are already available; mostly based on post-quantum and quantum…
Traditional cybersecurity methodologies target deterministic systems and fail to address the probabilistic nature of AI, leaving systems vulnerable to attack vectors such as model inversion, data poisoning, and prompt injection. Recent…
The quantum threat to cybersecurity has accelerated the standardization of Post-Quantum Cryptography (PQC). Migrating legacy software to these quantum-safe algorithms is not a simple library swap, but a new software engineering challenge:…
When a threat is observed, one of the most important challenges is to choose the most appropriate and adequate timely decisions in response to the current and near future situation in order to have the least consequences and costs. Making…
Practical QKD modulators introduce correlations between consecutively emitted pulses due to bandwidth limitations, violating key assumptions underlying many security proof techniques. Here, we address this problem by introducing a simple…
The present paper shows a proposal of the characteristics Cloud Risk Assessment Models should have and presents the review of the literature considering those characteristics in order to identify current gaps. This work shows a ranking of…
Detection of malicious activities in corporate environments is a very complex task and much effort has been invested into research of its automation. However, vast majority of existing methods operate only in a narrow scope which limits…
This paper addresses the challenge of model uncertainty in quantitative finance, where decisions in portfolio allocation, derivative pricing, and risk management rely on estimating stochastic models from limited data. In practice, the…
Sparse optimization problems are ubiquitous in many fields such as statistics, signal/image processing and machine learning. This has led to the birth of many iterative algorithms to solve them. A powerful strategy to boost the performance…
The rapid integration of Large Language Models (LLMs) across diverse sectors has marked a transformative era, showcasing remarkable capabilities in text generation and problem-solving tasks. However, this technological advancement is…
The development of Autonomous Vehicles (AV) presents an opportunity to save and improve lives. However, achieving SAE Level 5 (full) autonomy will require overcoming many technical challenges. There is a gap in the literature regarding the…
Wireless Federated Learning (FL) is an emerging distributed machine learning paradigm, particularly gaining momentum in domains with confidential and private data on mobile clients. However, the location-dependent performance, in terms of…
[Background] The rapidly changing business environments in which many companies operate is challenging traditional Requirements Engineering (RE) approaches. This gave rise to agile approaches for RE. Security, at the same time, is an…
The widespread adoption and increasing prominence of large language models (LLMs) in global technologies necessitate a rigorous focus on ensuring their safety across a diverse range of linguistic and cultural contexts. The lack of a…
Software security vulnerabilities can lead to severe consequences, making early detection essential. Although code review serves as a critical defense mechanism against security flaws, relevant feedback remains scarce due to limited…