Scalable model‐based configuration management of security services in complex enterprise networks

Security administrators face the challenge of designing, deploying and maintaining a variety of configuration files related to security systems, especially in large‐scale networks. These files have heterogeneous syntaxes and follow differing semantic concepts. Nevertheless, they are interdependent due to security services having to cooperate and their configuration to be consistent with each other, so that global security policies are completely and correctly enforced. To tackle this problem, our approach supports a comfortable definition of an abstract high‐level security policy and provides an automated derivation of the desired configuration files. It is an extension of policy‐based management and policy hierarchies, combining model‐based management (MBM) with system modularization. MBM employs an object‐oriented model of the managed system to obtain the details needed for automated policy refinement. The modularization into abstract subsystems (ASs) segment the system—and the model—into units which more closely encapsulate related system components and provide focused abstract views. As a result, scalability is achieved and even comprehensive IT systems can be modelled in a unified manner. The associated tool MoBaSeC (Model‐Based‐Service‐Configuration) supports interactive graphical modelling, automated model analysis and policy refinement with the derivation of configuration files. We describe the MBM and AS approaches, outline the tool functions and exemplify their applications and results obtained. Copyright © 2010 John Wiley & Sons, Ltd.     

Formal validation of automated policy refinement in the management of network security systems

Policy hierarchies and automated policy refinement are powerful approaches to simplify administration of security services in complex network environments. A crucial issue for the practical use of these approaches is to ensure the validity of the policy hierarchy, i.e. since the policy sets for the lower levels are automatically derived from the abstract policies (defined by the modeller), we must be sure that the derived policies uphold the high-level ones. This paper builds upon previous work on Model-based Management, particularly on the Diagram of Abstract Subsystems approach, and goes further to propose a formal validation approach for the policy hierarchies yielded by the automated policy refinement process. We establish general validation conditions for a multi-layered policy model, i.e. necessary and sufficient conditions that a policy hierarchy must satisfy so that the lower-level policy sets are valid refinements of the higher-level policies according to the criteria of consistency and completeness. Relying upon the validation conditions and upon axioms about the model representativeness, two theorems are proved to ensure compliance between the resulting system behaviour and the abstract policies that are modelled.     

Evaluation of Stereo Matching Costs on Images with Radiometric Differences

Stereo correspondence methods rely on matching costs for computing the similarity of image locations. We evaluate the insensitivity of different costs for passive binocular stereo methods with respect to radiometric variations of the input images. We consider both pixel-based and window-based variants like the absolute difference, the sampling-insensitive absolute difference, and normalized cross correlation, as well as their zero-mean versions. We also consider filters like LoG, mean, and bilateral background subtraction (BilSub) and nonparametric measures like Rank, SoftRank, Census, and Ordinal. Finally, hierarchical mutual information (HMI) is considered as pixelwise cost. Using stereo data sets with ground-truth disparities taken under controlled changes of exposure and lighting, we evaluate the costs with a local, a semiglobal, and a global stereo method. We measure the performance of all costs in the presence of simulated and real radiometric differences, including exposure differences, vignetting, varying lighting, and noise. Overall, the ranking of methods across all data sets and experiments appears to be consistent. Among the best costs are BilSub, which performs consistently very well for low radiometric differences; HMI, which is slightly better as pixelwise matching cost in some cases and for strong image noise; and Census, which showed the best and most robust overall performance.     

Pure Nash equilibria in player-specific and weighted congestion games

Unlike standard congestion games, weighted congestion games and congestion games with player-specific delay functions do not necessarily possess pure Nash equilibria. It is known, however, that there exist pure equilibria for both of these variants in the case of singleton congestion games, i.e., if the players’ strategy spaces contain only sets of cardinality one. In this paper, we investigate how far such a property on the players’ strategy spaces guaranteeing the existence of pure equilibria can be extended. We show that both weighted and player-specific congestion games admit pure equilibria in the case of matroid congestion games, i.e., if the strategy space of each player consists of the bases of a matroid on the set of resources. We also show that the matroid property is the maximal property that guarantees pure equilibria without taking into account how the strategy spaces of different players are interweaved.     

A TV Prior for High-Quality Scalable Multi-View Stereo Reconstruction

We present a scalable multi-view stereo method able to reconstruct accurate 3D models from hundreds of high-resolution input images. Local fusion of disparity maps obtained with semi-global matching enables the reconstruction of large scenes that do not fit into main memory. Since disparity maps may vary widely in quality and resolution, careful modeling of the 3D errors is crucial. We derive a sound stereo error model based on disparity uncertainty, which can vary spatially from tenths to several pixels. We introduce a feature based on total variation that allows pixel-wise classification of disparities into different error classes. For each class, we learn a disparity error distribution from ground-truth data using expectation maximization. We present a novel method for stochastic fusion of data with varying quality by adapting a multi-resolution volumetric fusion process that uses our error classes as a prior and models surface probabilities via an octree of voxels. Conflicts during surface extraction are resolved using visibility constraints and preference for voxels at higher resolutions. Experimental results on several challenging large-scale datasets demonstrate that our method yields improved performance both qualitatively and quantitatively.     

Model based testing in incremental system development

The spiraling nature of evolutionary software development processes produces executable parts of the system at the end of each loop. It is argued that these parts should consist not only of programming language code, but of executable graphical system models. As a main benefit of the use of more abstract, yet formal, modeling languages, a method for model based test sequence generation for reactive systems on the grounds of Constraint Logic Programming as well as its implementation in the CASE tool A F is presented.     

Effect of Al<Superscript>3+</Superscript> modification on cobalt ferrite and its impact on the magnetoelectric effect in BCZT–CFO multiferroic composites

One of the methods to enhance the functional properties of two-phase multiferroic magnetoelectrics is to increase magnetostriction of the ferrite phase. Al³⁺-modified cobalt ferrite Co(Al_0.5Fe_1.5)O₄ shows better magnetostriction than unmodified cobalt ferrite. It is used in combination with (Ba,Ca)(Zr,Ti)O₃ which has very good piezoelectric properties, to form a multiferroic composite. The composite shows good magnetoelectric characteristics, both macroscopically (converse magnetoelectric coefficient of 11 ps/m) and microscopically. Al³⁺ proves to be the best non-magnetic dopant to enhance magnetostriction in CoFe₂O₄ and thus the magnetoelectric coefficient.     

Scale-Free Registrations in 3D: 7 Degrees of Freedom with Fourier Mellin SOFT Transforms

Fourier Mellin SOFT (FMS) as a novel method for global registration of 3D data is presented. It determines the seven degrees of freedom (7-DoF) transformation, i.e., the 6-DoF rigid motion parameters plus 1-DoF scale, between two scans, i.e., two noisy, only partially overlapping views on objects or scenes. It is based on a sequence of the 3D Fourier transform, the Mellin transform and the SO(3) Fourier transform. This combination represents a non-trivial complete 3D extension of the well known Fourier-Mellin registration for 2D images. It is accordingly based on decoupling rotation and scale from translation. First, rotation—which is the main challenge for the extension to 3D data - is tackled with a SO(3) Fourier Transform (SOFT) based on Spherical Harmonics. In a second step, scale is determined via a 3D Mellin transform. Finally, translation is calculated by Phase-Matching. Experiments are presented with simulated data sets for ground truth comparisons and with real world data including object recognition and localization in Magnetic Resonance Tomography (MRT) data, registration of 2.5D RGBD scans from a Microsoft Kinect with a scale-free 3D model generated by Multi-View Vision, and 3D mapping by registration of a sequence of consecutive scans from a low-cost actuated Laser Range Finder. The results show that the method is fast and that it can robustly handle partial overlap, interfering structures, and noise. It is also shown that the method is a very interesting option for 6-DoF registration, i.e., when scale is known.