Related papers: Multicriteria Evaluation and Sensitivity Analysis …
Healthcare Information Technology (IT) has made great advances over the past few years and while these advances have enable healthcare professionals to provide higher quality healthcare to a larger number of individuals it also provides the…
As machine learning (ML) systems increasingly permeate high-stakes settings such as healthcare, transportation, military, and national security, concerns regarding their reliability have emerged. Despite notable progress, the performance of…
In this thesis we consider the problem of information hiding in the scenarios of interactive systems, statistical disclosure control, and refinement of specifications. We apply quantitative approaches to information flow in the first two…
Identifying, analyzing, and evaluating cybersecurity risks are essential to assess the vulnerabilities of modern manufacturing infrastructures and to devise effective decision-making strategies to secure critical manufacturing against…
We show how to use aspect-oriented programming to separate security and trust issues from the logical design of mobile, distributed systems. The main challenge is how to enforce various types of security policies, in particular predictive…
There are two strategic and longstanding questions about cyber risk that organizations largely have been unable to answer: What is an organization's estimated risk exposure and how does its security compare with peers? Answering both…
Security is a hot issue to be discussed, ranging from business activities, correspondence, banking and financial activities; it requires prudence and high precision. Since information security has a very important role in supporting…
Security-critical system requirements are increasingly enforced through mandatory access control systems. These systems are controlled by security policies, highly sensitive system components, which emphasizes the paramount importance of…
Industrial control systems (ICS) of critical infrastructure are increasingly connected to the Internet for remote site management at scale. However, cyber attacks against ICS - especially at the communication channels between humanmachine…
Vulnerability of Frontier language models to misuse and jailbreaks has prompted the development of safety measures like filters and alignment training in an effort to ensure safety through robustness to adversarially crafted prompts. We…
In the aftermath of the financial crisis, the growing literature on financial networks has widely documented the predictive power of topological characteristics (e.g. degree centrality measures) to explain the systemic impact or systemic…
Cyber assurance, which is the ability to operate under the onslaught of cyber attacks and other unexpected events, is essential for organizations facing inundating security threats on a daily basis. Organizations usually employ multiple…
Stealth attacks pose potential risks to cyber-physical systems because they are difficult to detect. Assessing the risk of systems under stealth attacks remains an open challenge, especially in nonlinear systems. To comprehensively quantify…
Organizations are increasingly targeted by Advanced Persistent Threats (APTs), which involve complex, multi-stage tactics and diverse techniques. Cyber Threat Intelligence (CTI) sources, such as incident reports and security blogs, provide…
Document-level Sentiment Analysis (DSA) is more challenging due to vague semantic links and complicate sentiment information. Recent works have been devoted to leveraging text summarization and have achieved promising results. However,…
In today's evolving threat landscape, ensuring digital sovereignty has become mandatory for military organizations, especially given their increased development and investment in AI-driven cyber security solutions. To this end, a…
The ongoing penetration of energy systems with information and communications technology (ICT) and the introduction of new markets increase the potential for malicious or profit-driven attacks that endanger system stability. To ensure…
Machine learning algorithms are increasingly used for consequential decision making regarding individuals based on their relevant features. Features that are relevant for accurate decisions may however lead to either explicit or implicit…
Artificial intelligence systems are prevalent in everyday life, with use cases in retail, manufacturing, health, and many other fields. With the rise in AI adoption, associated risks have been identified, including privacy risks to the…
Analysis of longitudinal randomised controlled trials is frequently complicated because patients deviate from the protocol. Where such deviations are relevant for the estimand, we are typically required to make an untestable assumption…