Custody plays a fundamental role for organizations and individuals seeking to access crypto assets (e.g., cryptocurrencies) and decentralized finance (DeFi) applications. Custodians store private keys and approve and sign transactions. Crypto asset transactions must be performed efficiently and securely to prevent a ny losses or theft of the assets. This paper presents a survey and taxonomy of the state-of-the-art solutions for this custody problem, highlighting their various features, as well as the open challenges that must be addressed.

The COVID-19 pandemic has recently emerged as a worldwide health emergency that necessitates coordinated international measures. To contain the virus's spread, governments and health organisations raced to develop vaccines that would lower Covid-19 morbidity, relieve pressure on healthcare systems, and allow economies to open. Following the COVID-19 vaccine, the vaccination certificate has been adopted to help the authorities formulate policies by controlling cross-border travelling. To address serious privacy concerns and eliminate the need for third parties to retain the trust and govern user data, in this paper, we leverage blockchain technologies in developing a secure and verifiable vaccination certificate. Our approach has the advantage of utilising a hybrid approach that implements different advanced technologies, such as the self-sovereignty concept, smart contracts and interPlanetary File System (IPFS). We rely on verifiable credentials paired with smart contracts to make decisions about who can access the system and provide on-chain verification and validation of the user and issuer DIDs. The approach was further analysed, with a focus on performance and security. Our analysis shows that our solution satisfies the security requirements for immunisation certificates.

Threat information sharing is considered as one of the proactive defensive approaches for enhancing the over-all security of trusted partners. Trusted partner organizations can provide access to past and current cybersecurity threats for reducing the risk of a potential cyberattack—the requirements for threat information sharing range from simplistic sharing of documents to threat intelligence sharing. Therefore, the storage and sharing of highly sensitive threat information raises considerable concerns regarding constructing a secure, trusted threat information exchange infrastructure. Establishing a trusted ecosystem for threat sharing will promote the validity, security, anonymity, scalability, latency efficiency, and traceability of the stored information that protects it from unauthorized disclosure. This paper proposes a system that ensures the security principles mentioned above by utilizing a distributed ledger technology that provides secure decentralized operations through smart contracts and provides a privacy-preserving ecosystem for threat information storage and sharing regarding the MITRE ATT&CK framework.

In a perfect world, coordination and cooperation across distributed autonomous systems would be a trivial task. However, incomplete information, malicious actors and real-world conditions can provide challenges which bring the trust-worthiness of participants into question. In this work-in-progress paper, we propose the novel use of Distributed Ledger Technologies with a particular focus on IOTA to provide a trust overlay governing information interchange across autonomous vehicles. This paper outlines a number of scenarios where information interchange could provide useful data for decision making, defines how trust can be useful in this context, and provides use cases which call for evaluating the trustworthiness of the message. The paper also outlines the architecture of an IOTA-based private tangle integrated with vehicle simulation software which facilitates the evaluation of various scenarios.

The growing trend of sharing news/contents, through social media platforms and the World Wide Web has been seen to impact our perception of the truth, altering our views about politics, economics, relationships, needs and wants. This is because of the growing spread of misinformation and disinformation intentionally or unintentionally by individuals and organizations. This trend has grave political, social, ethical, and privacy implications for society due to 1) the rapid developments in the field of Machine Learning (ML) and Deep Learning (DL) algorithms in creating realistic-looking yet fake digital content (such as text, images, and videos), 2) the ability to customize the content feeds and to create a polarized so-called "filter-bubbles" leveraging the availability of the big-data. Therefore, there is an ethical need to combat the flow of fake content. This paper attempts to resolves some of the aspects of this combat by presenting a high-level overview of TRUSTD, a blockchain and collective signature based ecosystem to help content creators in getting their content backed by the community, and to help users judge on the credibility and correctness of these contents.

In a pervasive environment, it is essential for computing applications to be context-aware. However, one of the major challenges is the establishment of a generic and dynamic context model. Many different approaches to modeling the context exist, but an application- and domain-agnostic context model, that captures various types of context information and the dependencies between them, that could be reused and shared by different applications, and that can be dynamically changed when a shift in focus occurs, is missing. Therefore, we are interested in defining a structure for the dynamic management of context information. This paper describes our notion of context and proposes a distributed context management architecture that supports the development of context-aware applications. It presents CANDEL, a generic context information representation framework that considers the context as a dynamic product line composed of context primitives (CPs). Frame based software product line techniques are used together with OWL ontology to define CPs and to dynamically generate the current context model. Further, using Petri-Nets, we also show how this framework will be used to support context-aware adaptive pervasive applications.

Context-awareness and adaptability are important and desirable properties of service-based processes designed to provide personalized services. Most of the existing approaches focus on the adaptation at the process instance level which involves extending the standard Business Process Execution Language (BPEL) and its engine or creating their own process languages (e.g. However, the approach proposed here aims to apply an adaptation to processes modeled or developed without any adaptation possibility in mind and independently of specific usage contexts. In addition, most of the existing approaches tackle the adaptation on the process instance or definition levels by explicitly specifying some form of variation points. This, however, leads to a contradiction between how the architect logically views and interprets differences in the process family and the actual modeling constructs through which the logical differences must be expressed. We introduce the notion of an evolution fragment and evolution primitive to capture the variability in a more logical and independent way. Finally, the proposed approach intends to support the viewpoint of context-aware adaptation as a crosscutting concern with respect to the core “business logic” of the process. In this way, the design of the process core can be decoupled from the design of the adaptation logic. To this end, we leverage ideas from the domain of model-driven development (MDD) and generative programming.

Context-aware computing is widely accepted as a promising paradigm to enable seamless computing. Several middlewares and ontology-based models for describing context information have been developed in order to support context-aware applications. However, the context variability, which refers to the possibility to infer or interpret different context information from different perspectives, has been neglected in the existing context modeling approaches. This paper presents an approach for context-aware software development based on a flexible product line based context model which significantly enhances reusability of context information by providing context variability constructs to satisfy different application needs.

The evolving concepts of mobile computing, context-awareness, and ambient intelligence are increasingly influencing user's experience of services. Therefore, the goal of this paper is to provide an overview of recent developments and implementations of middleware-based pervasive systems, and to explore major challenges of implementing such systems. This paper also provides a comprehensive access to the literature of the emerging approaches and design strategies of middleware for providing users with personalized services taking into consideration their preferences and the overall operating context. Middleware systems were categorized according to their internal coordination model.