Backscatter from the data plane – Threats to stability and security in information-centric network infrastructure

Information-centric networking (ICN) raises data objects to first class routable entities in the network and changes the Internet paradigm from host-centric connectivity to data-oriented delivery. However, current approaches to content routing heavily rely on data-driven protocol events and thereby introduce a strong coupling of the control to the data plane in the underlying routing infrastructure. In this paper, threats to the stability and security of the content distribution system are analyzed in theory, simulations, and practical experiments. We derive relations between state resources and the performance of routers, and demonstrate how this coupling can be misused in practice. We further show how state-based forwarding tends to degrade by decorrelating resources. We identify intrinsic attack vectors present in current content-centric routing, as well as possibilities and limitations to mitigate them. Our overall findings suggest that major architectural refinements are required prior to global ICN deployment in the real world.     

Spatial inverse query processing

Traditional spatial queries return, for a given query object q, all database objects that satisfy a given predicate, such as epsilon range and k-nearest neighbors. This paper defines and studies inverse spatial queries, which, given a subset of database objects Q and a query predicate, return all objects which, if used as query objects with the predicate, contain Q in their result. We first show a straightforward solution for answering inverse spatial queries for any query predicate. Then, we propose a filter-and-refinement framework that can be used to improve efficiency. We show how to apply this framework on a variety of inverse queries, using appropriate space pruning strategies. In particular, we propose solutions for inverse epsilon range queries, inverse k-nearest neighbor queries, and inverse skyline queries. Furthermore, we show how to relax the definition of inverse queries in order to ensure non-empty result sets. Our experiments show that our framework is significantly more efficient than naive approaches.     

Numerical simulation of cloud droplet formation in a tank

Using the computational fluid dynamics (CFD) code FLUENT 6 together with the fine particle model (FPM), numerical simulations of droplet dynamics in a 12.4 m³ cloud tank were conducted. The coupled fields of water vapor, temperature, flow velocity, particle number concentration, and particle mass concentration inside the cloud tank were computed.The system responses to changes of the wall's temperature and mass fraction of water vapor, respectively, were investigated. Typical times for mixing the cloud tank's contents are in the range of some tens of seconds. The maximum volume-averaged deviations from the mean of temperature and mass fraction of water vapor are around 5% of the respective parameter changes applied to the wall.Time-dependent simulations were performed in order to study the growth of ammonium-sulfate particles in humid air at around room temperature. Supersaturation up to (S_w–1)=8.2×10⁻³ was achieved by the expansion of the gas. The particles were activated and grew rapidly to a maximum diameter of 5.2×10⁻⁶ m after critical supersaturation was reached. After S_w fell again below the equilibrium value, the particles shrank quickly and deactivated roughly 60 s after activation.The spatial inhomogeneities of temperature and water-vapor concentration cause volume-averaged deviations of the particle number N and diameter d_g of up to 2.3% and 36%, respectively.     

Inversion handling for stable deformable modeling

In 3D deformable modeling approaches based on FEM, inverted tetrahedral elements can cause undesired visual artifacts and the breakdown of the simulation. As inversion can never be avoided and sometimes is even the correct behavior of elements, there is a strong need for stable inversion handling. In this paper, we propose a novel method to resolve inverted elements which is motivated by previous work of Irving et al. [6]. In combination with an efficient handling of degenerated elements, our approach yields a stable simulation of arbitrary deformations. Although we focus on the corotational formulation of linear FEM, the method can be implemented within arbitrary constitutive models.     

Generation of optimal artificial neural networks using a pattern search algorithm: application to approximation of chemical systems

A pattern search optimization method is applied to the generation of optimal artificial neural networks (ANNs). Optimization is performed using a mixed variable extension to the generalized pattern search method. This method offers the advantage that categorical variables, such as neural transfer functions and nodal connectivities, can be used as parameters in optimization. When used together with a surrogate, the resulting algorithm is highly efficient for expensive objective functions. Results demonstrate the effectiveness of this method in optimizing an ANN for the number of neurons, the type of transfer function, and the connectivity among neurons. The optimization method is applied to a chemistry approximation of practical relevance. In this application, temperature and a chemical source term are approximated as functions of two independent parameters using optimal ANNs. Comparison of the performance of optimal ANNs with conventional tabulation methods demonstrates equivalent accuracy by considerable savings in memory storage. The architecture of the optimal ANN for the approximation of the chemical source term consists of a fully connected feedforward network having four nonlinear hidden layers and 117 synaptic weights. An equivalent representation of the chemical source term using tabulation techniques would require a 500 x 500 grid point discretization of the parameter space.     

SEMPA – Ein Ansatz des Semantischen Prozessmanagements zur Planung von Prozessmodellen

Currently process modeling is mostly done manually. Therefore, the initial design of process models as well as changes to process models which are frequently necessary to react to new market developments or new regulations are time-consuming tasks. In this paper we introduce SEMPA, an approach for the partly automatic planning of process models. Using ontologies to semantically describe actions – as envisioned in Semantic Business Process Management –, a process model for a specified problem setting can be created automatically. In comparison to existing planning algorithms our approach creates process models including control structures and is able to cope with complex and numerical input and output parameters of actions. The prototypical implementation as well as an example taken from the financial services domain illustrate the practical benefit of our approach.     

Bringing law and order to IEEE 802.11 networks—A case for DiscoSec

To improve the tarnished reputation of WLAN security, the new IEEE 802.11i standard provides means for mutual user authentication and assures confidentiality of user data. However, the IEEE 802.11 link-layer is still highly vulnerable to a plethora of simple, yet effective attacks which further jeopardize the already fragile security of wireless communications.Some of these vulnerabilities are related to limited hardware capabilities of access points and their abuse may result in serious degradation of control over the wireless connection, which, especially in the case of broadcast communication, allows for client hijacking attacks. Although these issues are known and their impact is expected to be less prevalent on modern equipment, this work demonstrates the opposite. In our experimental analysis, we tested frequently used access points, and by forcing them to operate on their performance limits, we identified significant operational anomalies and demonstrated their impact on security by implementing a novel version of the Man-In-The-Middle attack, to which we refer as the Muzzle attack.Secondly, this work describes DiscoSec, a solution for “patching” WLANs against a variety of such link-layer attacks. DiscoSec provides DoS-resilient key exchange, an efficient frame authentication, and a performance-oriented implementation. By means of extensive real-world measurements DiscoSec is evaluated, showing that even on very resource-limited devices the network throughput is decreased by only 22% compared to the throughput without any authentication, and by 6% on more performance-capable hardware. To demonstrate its effectiveness, DiscoSec is available as an open-source IEEE 802.11 device driver utilizing well-established cryptographic primitives provided by the Linux Crypto API and OpenSSL library.     

The process map as an instrument to standardize processes: design and application at a financial service provider

The standardization of processes and the identification of shared business services in a service-oriented architecture (SOA) are currently widely discussed. Above all in practice, however, there still is a lack of appropriate instruments to support these tasks. In this paper an approach for a process map is introduced which allows for a systematic presentation—as complete as possible—of the processes in an enterprise (division). After a consistent refinement of the process has taken place by means of aggregation/disaggregation respectively, generalization/specialization relations, it is possible to identify primarily functional similarities of the detailed sub-processes. The application of the process map at a financial service provider (FSP) highlights how these similarities can be taken as a basis to standardize processes and to identify shared services.     

Perfect sequence excitation of the NLMS algorithm and its application to acoustic echo control

Adaptive echo cancellers are currently being studied for applications such as audio teleconference systems or hands-free telephone sets with high speech quality. The purpose of the echo control is to eliminate the acoustic feedback from the loudspeaker to the microphone. One problem of echo cancellers using e.g. the normalized least mean square algorithm(nlms) for the adaptation of the coefficients is that the convergence properties degrade with colored signal input such as speech signals [8, 9, 17]. One approach to accelerate the convergence speed is to introduce linear prediction filters in order to decorrelate the speech signal [1, 2, 12, 15, 20]. This paper presents a new approach, named the excited lms algorithm orelms algorithm, which prewhitens the input signal applying perfect sequences. Coincidently, the proposed algorithm can be interpreted as a combination of the conventionalnlms algorithm and a system identification approach using m-sequences or related sequences.