Trust Evaluation for Embedded Systems Security research challenges identified from an incident network scenario

This paper is about trust establishment and trust evaluations techniques. A short background about trust, trusted computing and security in embedded systems is given. An analysis has been done of an incident network scenario with roaming users and a set of basic security needs has been identified. These needs have been used to derive security requirements for devices and systems, supporting the considered scenario. Using the requirements, a list of major security challenges for future research regarding trust establishment in dynamic networks have been collected and elaboration on some different approaches for future research has been done.This work was supported by the Knowledge foundation and RISE within the ARIES project

Artificial Intelligence and Patient-Centered Decision-Making

Advanced AI systems are rapidly making their way into medical research and practice, and, arguably, it is only a matter of time before they will surpass human practitioners in terms of accuracy, reliability, and knowledge. If this is true, practitioners will have a prima facie epistemic and professional obligation to align their medical verdicts with those of advanced AI systems. However, in light of their complexity, these AI systems will often function as black boxes: the details of their contents, calculations, and procedures cannot be meaningfully understood by human practitioners. When AI systems reach this level of complexity, we can also speak of black-box medicine. In this paper, we want to argue that black-box medicine conflicts with core ideals of patient-centered medicine. In particular, we claim, black-box medicine is not conducive for supporting informed decision-making based on shared information, shared deliberation, and shared mind between practitioner and patient

Faster Fully-Dynamic Minimum Spanning Forest

We give a new data structure for the fully-dynamic minimum spanning forest problem in simple graphs. Edge updates are supported in $O(\log^4n/\log\log n)$ amortized time per operation, improving the $O(\log^4n)$ amortized bound of Holm et al. (STOC'98, JACM'01). We assume the Word-RAM model with standard instructions.Comment: 13 pages, 2 figure

Using parallel computation to improve Independent Metropolis--Hastings based estimation

In this paper, we consider the implications of the fact that parallel raw-power can be exploited by a generic Metropolis--Hastings algorithm if the proposed values are independent. In particular, we present improvements to the independent Metropolis--Hastings algorithm that significantly decrease the variance of any estimator derived from the MCMC output, for a null computing cost since those improvements are based on a fixed number of target density evaluations. Furthermore, the techniques developed in this paper do not jeopardize the Markovian convergence properties of the algorithm, since they are based on the Rao--Blackwell principles of Gelfand and Smith (1990), already exploited in Casella and Robert (1996), Atchade and Perron (2005) and Douc and Robert (2010). We illustrate those improvements both on a toy normal example and on a classical probit regression model, but stress the fact that they are applicable in any case where the independent Metropolis-Hastings is applicable.Comment: 19 pages, 8 figures, to appear in Journal of Computational and Graphical Statistic

Sources of Regional Resilience in the Danish ICT Sector

In this paper the use of the term “resilience” is discussed and a definition for use in quantitative studies of industrial evolution is suggested. Resilience is the ability of an industry in a region to exploit the possibilities arising from external events and adapt to thrive under new selection environments. An econometric analysis is undertaken to uncover the effects of the change in selection environment that the ICT industry faced from the burst of the ICT bubble in the year 2000. It is shown that some characteristics of regional industry structure are associated with growth over the whole period while other characteristics have varying effects pre and post burst. Special attention is given to the responsiveness of growth to the evolution of sales of ICT goods and services in Denmark and it is found that the industry structures that restrain growth also are the ones, which make the regional industry better able to exploit changes in sales at the national level.Resilience; Business cycle; ICT sector; Regional growth

Toward more realistic analytic models of the heliotail: Incorporating magnetic flattening via distortion flows

Both physical arguments and simulations of the global heliosphere indicate that the tailward heliopause is flattened considerably in the direction perpendicular to both the incoming flow and the large-scale interstellar magnetic field. Despite this fact, all of the existing global analytical models of the outer heliosheath's magnetic field assume a circular cross section of the heliotail. To eliminate this inconsistency, we introduce a mathematical procedure by which any analytically or numerically given magnetic field can be deformed in such a way that the cross sections along the heliotail axis attain freely prescribed, spatially dependent values for their total area and aspect ratio. The distorting transformation of this method honors both the solenoidality condition and the stationary induction equation with respect to an accompanying flow field, provided that both constraints were already satisfied for the original magnetic and flow fields prior to the transformation. In order to obtain realistic values for the above parameters, we present the first quantitative analysis of the heliotail's overall distortion as seen in state-of-the-art three-dimensional hybrid MHD-kinetic simulations.Comment: 15 pages, 8 figures. Published in The Astrophysical Journa

Non-convex Global Minimization and False Discovery Rate Control for the TREX

The TREX is a recently introduced method for performing sparse high-dimensional regression. Despite its statistical promise as an alternative to the lasso, square-root lasso, and scaled lasso, the TREX is computationally challenging in that it requires solving a non-convex optimization problem. This paper shows a remarkable result: despite the non-convexity of the TREX problem, there exists a polynomial-time algorithm that is guaranteed to find the global minimum. This result adds the TREX to a very short list of non-convex optimization problems that can be globally optimized (principal components analysis being a famous example). After deriving and developing this new approach, we demonstrate that (i) the ability of the preexisting TREX heuristic to reach the global minimum is strongly dependent on the difficulty of the underlying statistical problem, (ii) the new polynomial-time algorithm for TREX permits a novel variable ranking and selection scheme, (iii) this scheme can be incorporated into a rule that controls the false discovery rate (FDR) of included features in the model. To achieve this last aim, we provide an extension of the results of Barber & Candes (2015) to establish that the knockoff filter framework can be applied to the TREX. This investigation thus provides both a rare case study of a heuristic for non-convex optimization and a novel way of exploiting non-convexity for statistical inference