In search of self-sovereign identity leveraging blockchain technology

In recent times, with the advent of blockchain technology, there is an optimism surrounding the concept of self-sovereign identity which is regarded to have an influential effect on how we interact with each other over the Internet in future. There are a few works in the literature which examine different aspects of self-sovereign identity. Unfortunately, the existing works are not methodological and comprehensive at all. Moreover, there exist different notions of what the term self-sovereign identity means. To exploit its full potential, it is essential to ensure a common understanding in a formal way. This paper aims to achieve this goal by providing the first-ever formal and rigorous treatment of the concept of self-sovereign identity using a mathematical model. This paper examines the properties that a self-sovereign identity should have and explores the impact of self-sovereign identity over the laws of identity. It also highlights the essential life-cycles of an identity management system and inter-relates how the notion of self-sovereign identity can be applied in these life-cycles. In addition, the paper illustrates several envisioned flows involving a self-sovereign identity leveraging blockchain technology covering different aspects of an identity management system. All in all, this paper presents the first formal and comprehensive step toward an academic investigation of self-sovereign identity

Indirect neural-based finite-time integral sliding mode control for trajectory tracking guidance of Mars entry vehicle

This article presents an indirect neural-based finite-time integral sliding mode control algorithm for the reference trajectory tracking guidance of Mars entry vehicle under uncertainties. The proposed controller is developed as a combination of finite-time integral sliding mode controller and indirect neural identification. The finite-time integral sliding mode controller is designed by constructing a new type of finite-time integral sliding mode surface to prevent the singularity problem. Moreover, the neural network (NN) is combined with the finite-time integral sliding mode controller to identify the lumped uncertainty and attenuate the chattering phenomenon. Particularly, the concept of indirect neural identification is adopted and only a single adaptive parameter is required to be learned online. In this way, the proposed controller is not only strongly robust against aerodynamic and density uncertainties, but also computationally simple for onboard implementations. Stability argument indicates that the proposed controller can ensure the radial distance tracking error and its time differentiation regulate to the small residual sets around zero in finite time. Lastly, the effectiveness and excellent guidance performance of the proposed control algorithm are demonstrated through simulation studies on a Mars Science Laboratory-type (MSL-type) entry vehicle

A validation of security determinants model for cloud adoption in Saudi organisations’ context

Governments across the world are starting to make a dynamic shift to cloud computing so as to increase efficiency. Although, the cloud technology brings various benefits for government organisations, including flexibility and low cost, adopting it with the existing system is not an easy task. In this regard, the most significant challenge to any government agency is security concern. Our previous study focused to identify security factors that influence decision of government organisations to adopt cloud. This research enhances the previous work by investigating on the impact of various independent security related factors on the adopted security taxonomy based on critical ratio, standard error and significance levels. Data was collected from IT and security experts in the government organisations of Saudi Arabia. The Analysis of Moment Structures (AMOS) tool was used in this research for data analysis. Critical ratio reveals the importance of Security Benefits, Risks and Awareness Taxonomies on cloud adoption. Also, most of the exogenous variables had strong and positive relationships with their fellow exogenous variables. In future, this taxonomy model can also be applied for studying the adoption of new IT innovations whose IT architecture is similar to that of the cloud.N/