Model comprehension for security risk assessment: an empirical comparison of tabular vs. graphical representations

Tabular and graphical representations are used to communicate security risk assessments for IT systems. However, there is no consensus on which type of representation better supports the comprehension of risks (such as the relationships between threats, vulnerabilities and security controls). Cognitive fit theory predicts that spatial relationships should be better captured by graphs. In this paper we report the results of two studies performed in two countries with 69 and 83 participants respectively, in which we assessed the effectiveness of tabular and graphical representations with respect to extraction correct information about security risks. The experimental results show that tabular risk models are more effective than the graphical ones with respect to simple comprehension tasks and in some cases are more effective for complex comprehension tasks. We explain our findings by proposing a simple extension of Vessey’s cognitive fit theory as some linear spatial relationships could be also captured by tabular models.     

Electroosmotic flow through an $$\alpha$$-hemolysin nanopore

Nanopores are emerging as powerful tools for biosensing at a single molecule level, and their characterization under different working conditions is crucial for applications. In this perspective, we studied the ionic and electroosmotic flows across an \(\alpha\)-hemolysin nanopore using an extensive set of molecular dynamics simulations. Results show that the alteration in the solution pH has a dramatic effect on both electroosmotic flow and nanopore selectivity. Upon lowering the pH, the internal pore surface becomes globally more positively charged and, consequently, the transport of positive ions is hindered leading to a strong unbalance of positive and negative ionic fluxes. This unbalance gives rise to an intense electroosmotic flow that in certain regimes can overwhelm the ionic flux. Finally, we compared our data with continuum prediction for ideal electroosmotic flows, showing that, although the \(\alpha\)-hemolysin case is quite far from the ideality, the continuum theory is able to capture the magnitude of the electroosmotic mechanism.     

A comparison of static,dynamic, and hybrid analysis for malware detection

In this research, we compare malware detection techniques based on static, dynamic, and hybrid analysis. Specifically, we train Hidden Markov Models (HMMs) on both static and dynamic feature sets and compare the resulting detection rates over a substantial number of malware families. We also consider hybrid cases, where dynamic analysis is used in the training phase, with static techniques used in the detection phase, and vice versa. In our experiments, a fully dynamic approach generally yields the best detection rates. We discuss the implications of this research for malware detection based on hybrid techniques.     

A numerical study concerning brain stroke detection by microwave imaging systems

In this paper, a numerical study devoted to evaluate the application of a microwave imaging method for brain stroke detection is described. First of all, suitable operating conditions for the imaging system are defined by solving the forward electromagnetic scattering problem with respect to simplified configurations and analyzing the interactions between an illuminating electromagnetic wave at microwave frequencies and the biological tissues inside the head. Then, preliminary inversion results are obtained by applying an imaging procedure based on an iterative Gauss-Newton scheme to a realistic model of the human head. The proposed imaging algorithm is able to deal with the nonlinear and ill-posed problem associated to the integral equations describing the inverse scattering problem. The aim of the inversion procedure is related to the determination of the presence of a hemorrhagic brain stroke by retrieving the distributions of the dielectric parameters of the human tissues inside a slice of the head model.     

State of the Art in Artistic Editing of Appearance,Lighting and Material

Mimicking the appearance of the real world is a longstanding goal of computer graphics, with several important applications in the feature film, architecture and medical industries. Images with well‐designed shading are an important tool for conveying information about the world, be it the shape and function of a computer‐aided design (CAD) model, or the mood of a movie sequence. However, authoring this content is often a tedious task, even if undertaken by groups of highly trained and experienced artists. Unsurprisingly, numerous methods to facilitate and accelerate this appearance editing task have been proposed, enabling the editing of scene objects' appearances, lighting and materials, as well as entailing the introduction of new interaction paradigms and specialized preview rendering techniques. In this review, we provide a comprehensive survey of artistic appearance, lighting and material editing approaches. We organize this complex and active research area in a structure tailored to academic researchers, graduate students and industry professionals alike. In addition to editing approaches, we discuss how user interaction paradigms and rendering back ends combine to form usable systems for appearance editing. We conclude with a discussion of open problems and challenges to motivate and guide future research.     

On the human perception of dissimilarities between postures of humanoids

This paper analyzes the perceived dissimilarity between postures of humanoid robots. First, the human perception of absolute distance between postures is focused. It is shown that results derived in computer graphics for human figures can be replicated with humanoids, despite the difference in body proportions and arrangement of the degrees of freedom. Successively, the perception of relative distances between postures is considered. It is shown that, paradoxically, better prediction of the distance between a pair of postures does not necessary lead to better predictions of which of multiple distances is the shortest. Finally, the paper concludes by briefly discussing possible implications of this finding to the fields of motion retrieval and motion blending.     

3D reconstruction for featureless scenes with curvature hints

We present a novel interactive framework for improving 3D reconstruction starting from incomplete or noisy results obtained through image-based reconstruction algorithms. The core idea is to enable the user to provide localized hints on the curvature of the surface, which are turned into constraints during an energy minimization reconstruction. To make this task simple, we propose two algorithms. The first is a multi-view segmentation algorithm that allows the user to propagate the foreground selection of one or more images both to all the images of the input set and to the 3D points, to accurately select the part of the scene to be reconstructed. The second is a fast GPU-based algorithm for the reconstruction of smooth surfaces from multiple views, which incorporates the hints provided by the user. We show that our framework can turn a poor-quality reconstruction produced with state of the art image-based reconstruction methods into a high- quality one.     

Exploiting label semantic relatedness for unsupervised image annotation with large free vocabularies

Automatic Image Annotation (AIA) is the task of assigning keywords to images, with the aim to describe their visual content. Recently, an unsupervised approach has been used to tackle this task. Unsupervised AIA (UAIA) methods use reference collections that consist of the textual documents containing images. The aim of the UAIA methods is to extract words from the reference collection to be assigned to images. In this regard, by using an unsupervised approach it is possible to include large vocabularies because any word could be extracted from the reference collection. However, having a greater diversity of words for labeling entails to deal with a larger number of wrong annotations, due to the increasing difficulty for assigning a correct relevance to the labels. With this problem in mind, this paper presents a general strategy for UAIA methods that reranks assigned labels. The proposed method exploits the semantic-relatedness information among labels in order to assign them an appropriate relevance for describing images. Experimental results in different benchmark datasets show the flexibility of our method to deal with assignments from free-vocabularies, and its effectiveness to improve the initial annotation performance for different UAIA methods. Moreover, we found that (1) when considering the semantic-relatedness information among the assigned labels, the initial ranking provided by a UAIA method is improved in most of the cases; and (2) the robustness of the proposed method to be applied on different UAIA methods, will allow extending capabilities of state-of-the-art UAIA methods.

     

Generalized XML security views

We investigate a generalization of the notion of XML security view introduced by Stoica and Farkas (Proceedings of the 16th International Conference on Data and Applications Security (IFIP’02). IFIP Conference Proceedings, vol. 256, pp. 133–146. Kluwer, Dordrecht, 2002) and later refined by Fan et al. (Proceedings of the ACM SIG- MOD International Conference on Management of Data (SIGMOD’04), pp. 587–598. ACM Press, New York, 2004). The model consists of access control policies specified over DTDs with XPath expressions for data-dependent access control. We provide the notion of security views characterizing information accessible to authorized users. This is a trans- formed DTD schema that can be used by users for query formulation. We develop an algorithm to materialize an authorized version of the document from the view and an algorithm to construct the view from an access control specification. We show that our view construction combined with materialization produces the same result as the direct application of the DTD access specification on the document. We also propose a number of generalizations of possible security policies and show how they affect view construction algorithm. Finally, we provide an evaluation of our system.