Related papers: The case for Zero Trust Digital Forensics

In this paper, we are concerned with trust modeling for agents in networked computing systems. As trust is a subjective notion that is invisible, implicit and uncertain in nature, many attempts have been made to model trust with aid of…

Trust models are widely used in various computer science disciplines. The main purpose of a trust model is to continuously measure trustworthiness of a set of entities based on their behaviors. In this article, the novel notion of "rational…

In the wake of a cybersecurity incident, it is crucial to promptly discover how the threat actors breached security in order to assess the impact of the incident and to develop and deploy countermeasures that can protect against further…

In the last decade, wireless sensor networks (WSNs) and Internet-of-Things (IoT) devices are proliferated in many domains including critical infrastructures such as energy, transportation and manufacturing. Consequently, most of the daily…

The main goal of this research project is to evaluate the effectiveness and speed of open-source forensic tools for digital evidence collecting from various Internet-of-Things (IoT) devices. The project will create and configure many IoT…

Digital Twins (DTs) are increasingly deployed across application domains, yet the treatment of trust-related issues remains unevenly addressed. To examine whether and how trust is discussed in the current landscape, we conducted a…

Event reconstruction is a fundamental part of the digital forensic process, helping to answer key questions like who, what, when, and how. A common way of accomplishing that is to use tools to create timelines, which are then analyzed.…

The collection and handling of court admissible evidence is a fundamental component of any digital forensic investigation. While the procedures for handling digital evidence take much of their influence from the established policies for the…

A critical step to building trustworthy deep neural networks is trust quantification, where we ask the question: How much can we trust a deep neural network? In this study, we take a step towards simple, interpretable metrics for trust…

Cloud computing is a rapidly evolving information technology (IT) phenomenon. Rather than procure, deploy and manage a physical IT infrastructure to host their software applications, organizations are increasingly deploying their…

Deepfakes are becoming increasingly credible, posing a significant threat given their potential to facilitate fraud or bypass access control systems. This has motivated the development of deepfake detection methods, in which deep learning…

Artificial Intelligence (AI) is becoming the corner stone of many systems used in our daily lives such as autonomous vehicles, healthcare systems, and unmanned aircraft systems. Machine Learning is a field of AI that enables systems to…

Digitalization is leading us towards a future where people, processes, data and things are not only interacting with each other, but might start forming societies on their own. In these dynamic systems enhanced by artificial intelligence,…

Inference using deep neural networks is often outsourced to the cloud since it is a computationally demanding task. However, this raises a fundamental issue of trust. How can a client be sure that the cloud has performed inference…

The increasing connectivity and intricate remote access environment have made traditional perimeter-based network defense vulnerable. Zero trust becomes a promising approach to provide defense policies based on agent-centric trust…

The financial crime landscape is evolving along with the digitization in financial services. In this context, laws and regulations cannot efficiently cope with a fast-moving industry such as finance, which translates in late adoption of…

Trust is a fundamental concept in large-scale distributed systems like the Internet of Things (IoT). Trust helps to resolve choices into a decision. However, the trust calculation depends on the amount of uncertainty present in data…

Trust is a fundamental concept in many real-world applications such as e-commerce and peer-to-peer networks. In these applications, users can generate local opinions about the counterparts based on direct experiences, and these opinions can…

Cloud computing has emerged as a popular computing paradigm in recent years. However, today's cloud computing architectures often lack support for computer forensic investigations. A key task of digital forensics is to prove the presence of…

Trust is a fundamental concept in human decision-making and collaboration that has long been studied in philosophy and psychology. However, software engineering (SE) articles often use the term trust informally; providing an explicit…