Quantifying DNS namespace influence

Name resolution using the Domain Name System (DNS) is integral to today’s Internet. The resolution of a domain name is often dependent on namespace outside the control of the domain’s owner. In this article we review the DNS protocol and several DNS server implementations. Based on our examination, we propose a formal model for analyzing the name dependencies inherent in DNS. Using our name dependency model we derive metrics to quantify the extent to which domain names affect other domain names. It is found that under certain conditions, more than half of the queries for a domain name are influenced by namespaces not expressly configured by administrators. This result serves to quantify the degree of vulnerability of DNS due to dependencies that administrators are unaware of. When we apply metrics from our model to production DNS data, we show that the set of domains whose resolution affects a given domain name is much smaller than previously thought. However, behaviors such as using cached addresses for querying authoritative servers and chaining domain name aliases increase the number and diversity of influential domains, thereby making the DNS infrastructure more vulnerable.     

Static output feedback control via PDE boundary and ODE measurements in linear cascaded ODE–beam systems

This paper addresses the problem of feedback control design for a class of linear cascaded ordinary differential equation (ODE)–partial differential equation (PDE) systems via a boundary interconnection, where the ODE system is linear time-invariant and the PDE system is described by an Euler–Bernoulli beam (EBB) equation with variable coefficients. The objective of this paper is to design a static output feedback (SOF) controller via EBB boundary and ODE measurements such that the resulting closed-loop cascaded system is exponentially stable. The Lyapunov’s direct method is employed to derive the stabilization condition for the cascaded ODE–beam system, which is provided in terms of a set of bilinear matrix inequalities (BMIs). Furthermore, in order to compute the gain matrices of SOF controllers, a two-step procedure is presented to solve the BMI feasibility problem via the existing linear matrix inequality (LMI) optimization techniques. Finally, the numerical simulation is given to illustrate the effectiveness of the proposed design method.     

Novel associative classifier based on dynamic adaptive PSO: Application to determining candidates for thoracic surgery

Association rule mining is a data mining technique for discovering useful and novel patterns or relationships from databases. These rules are simple to infer and intuitive and can be easily used for classification in any domain that requires explanation for and investigation into how the classification works. Examples of such areas are medicine, agriculture, education, etc. For such a system to find wide adoptability, it should give output that is correct and comprehensible. The amount of data has been growing very fast and so has the search space of these problems. So we need to change traditional methods. This paper discusses a rule mining classifier called DA-AC (dynamic adaptive-associative classifier) which is based on a Dynamic Particle Swarm Optimizer. Due to its seeding method, exemplar selection, adaptive parameters, dynamic reconstruction of regions and velocity update, it avoids premature convergence and provides a better value in every dimension. Quality evaluation is done both for individual rules as well as entire rulesets. Experiments were conducted over fifteen benchmark datasets to evaluate performance of proposed algorithm in comparison with six other state-of-the-art non associative classifiers and eight associative classifiers. Results demonstrate competitive performance of proposed DA-AC while considering predictive accuracy and number of mined patterns as parameters. The method was then applied to predict life expectancy of post operative thoracic surgery patients.     

An architectural design for effective information retrieval in semantic web

The current web IR system retrieves relevant information only based on the keywords which is inadequate for that vast amount of data. It provides limited capabilities to capture the concepts of the user needs and the relation between the keywords. These limitations lead to the idea of the user conceptual search which includes concepts and meanings. This study deals with the Semantic Based Information Retrieval System for a semantic web search and presented with an improved algorithm to retrieve the information in a more efficient way.This architecture takes as input a list of plain keywords provided by the user and the query is converted into semantic query. This conversion is carried out with the help of the domain concepts of the pre-existing domain ontologies and a third party thesaurus and discover semantic relationship between them in runtime. The relevant information for the semantic query is retrieved and ranked according to the relevancy with the help of an improved algorithm. The performance analysis shows that the proposed system can improve the accuracy and effectiveness for retrieving relevant web documents compared to the existing systems.     

Safety-based availability assessment at design stage

The availability of a system or equipment is one of the crucial characteristics that measures the customer satisfaction and strongly influences his final choice decision between concurrent products. The aim of this work is to provide an approach to improve the products availability assessment by taking into account the safety criteria by considering the use situations at design stage. Our work focuses on the routine design of complex products. The availability is often simply estimated considering reliability and maintainability. Basically, the intrinsic availability is the probability that it is operating satisfactorily at any point in time when used under conditions stated by design specifications. The time considered includes operating time and active repair time. Thus, intrinsic availability excludes from consideration all other times in the product lifecycle such as: accident management time, storage time, administrative time or logistic time. But many studies show that the loss of availability performance is also due to accidents that occur in different unforeseeable utilization situations. This engenders stops of the system to ensure the users safety according to standards recommendations. In this purpose, we consider the structural product architecture and the different use cases that correspond to the operational states and downtimes due to stop events that may happen during the utilization like failures, maintenance tasks and accidents. Then, we propose a product behavioral analysis including the use cases to describe interactions between the product and users or maintenance operators. We use Markov chains to model the use cases corresponding to operating time (OT), maintenance time (MT) and preparing time after accidents (RT). Then these three parameters are considered to specify a generic approach to improve the availability assessment. Such an approach provides the traceability of the product behavior along its lifecycle. In this way, the main causes of stop can be identified and this may guide the designer for improving the availability of the product future versions. To validate our approach, an application is presented considering a printing line. The comparison of our simulation considering an industrial case study shows a good agreement about the influence of safety on the availability.     

Improved migration for mobile computing in distributed networks

A mobile ad hoc network (MANET) is a special type of wireless network in which a collection of mobile nodes with wireless network interfaces may form a temporary network, without the aids of any fixed infrastructure. Security has become a hot research topic in mobile ad hoc networks. In 1998, Volker and Mehrdad proposed a tree-based key management and access control scheme for the mobile agents to manage rights to access its own resources for the visited mobile nodes. Latter, Huang et al. showed that Volker and Mehrdad's scheme needs a large amount of storage and costs for managing and storing secret keys. Huang et al. further proposed a new and efficient scheme based on the elliptic curve cryptosystems to reduce costs and gain better efficiency. However, there is a security leak inherent in Huang et al.'s scheme that the malicious node can overstep his authority to access unauthorized information. This paper will propose a secure, robust, and efficient hierarchical key management scheme for MANETs. Some practical issues and solutions about dynamic key management are also considered and proposed. As compared with Huang et al.'s scheme, our proposed scheme can provide better security assurance, while requiring smaller key-size, lower computational complexities, and constant key management costs which is independent on the number of the confidential files and the visited nodes.     

A standard for developing secure mobile applications

The abundance of mobile software applications (apps) has created a security challenge. These apps are widely available across all platforms for little to no cost and are often created by small companies and less-experienced programmers. The lack of development standards and best practices exposes the mobile device to potential attacks. This article explores not only the practices that should be adopted by developers of all apps, but also those practices the enterprise user should demand of any app that resides on a mobile device that is employed for both business and private uses.     

Recognizing activities in multiple views with fusion of frame judgments

This paper focuses on activity recognition when multiple views are available. In the literature, this is often performed using two different approaches. In the first one, the systems build a 3D reconstruction and match that. However, there are practical disadvantages to this methodology since a sufficient number of overlapping views is needed to reconstruct, and one must calibrate the cameras. A simpler alternative is to match the frames individually. This offers significant advantages in the system architecture (e.g., it is easy to incorporate new features and camera dropouts can be tolerated). In this paper, the second approach is employed and a novel fusion method is proposed. Our fusion method collects the activity labels over frames and cameras, and then fuses activity judgments as the sequence label. It is shown that there is no performance penalty when a straightforward weighted voting scheme is used. In particular, when there are enough overlapping views to generate a volumetric reconstruction, our recognition performance is comparable with that produced by volumetric reconstructions. However, if the overlapping views are not adequate, the performance degrades fairly gracefully, even in cases where test and training views do not overlap.     

Nonlinear multiobjective model-predictive control scheme for wastewater treatment process

A nonlinear multiobjective model-predictive control (NMMPC) scheme, consisting of self-organizing radial basis function (SORBF) neural network prediction and multiobjective gradient optimization, is proposed for wastewater treatment process (WWTP) in this paper. The proposed NMMPC comprises a SORBF neural network identifier and a multiple objectives controller via the multi-gradient method (MGM). The SORBF neural network with concurrent structure and parameter learning is developed as a model identifier for approximating on-line the states of WWTP. Then, this NMMPC optimizes the multiple objectives under different operating functions, where all the objectives are minimized simultaneously. The solution of optimal control is based on the MGM which can shorten the solution time. Moreover, the stability and control performance of the closed-loop control system are well studied. Numerical simulations reveal that the proposed control strategy gives satisfactory tracking and disturbance rejection performance for WWTP. Experimental results show the efficacy of the proposed method.     

L2 disturbance attenuation for highly dissipative nonlinear spatially distributed processes via HJI approach

For many practical industrial spatially distributed processes (SDPs), their dynamics are usually described by highly dissipative nonlinear partial differential equations (PDEs). In this paper, we address the L₂ disturbance attenuation problem of nonlinear SDPs using the Hamilton–Jacobi–Isaacs (HJI) approach. Firstly, by collecting an ensemble of PDE states, Karhunen–Loève decomposition (KLD) is employed to compute empirical eigenfunctions (EEFs) of the SDP based on the method of snapshots. Subsequently, these EEFs together with singular perturbation (SP) technique are used to obtain a finite-dimensional slow subsystem of ordinary differential equation (ODE) that accurately describes the dominant dynamics of the PDE system. Secondly, based on the slow subsystem, the L₂ disturbance attenuation problem is reformulated and a finite-dimensional H_∞ controller is synthesized in terms of the HJI equation. Moreover, the stability and L₂-gain performance of the closed-loop PDE system are analyzed. Thirdly, since the HJI equation is a nonlinear PDE that has proven to be impossible to solve analytically, we combine the method of weighted residuals (MWR) and simultaneous policy update algorithm (SPUA) to obtain its approximate solution. Finally, the simulation studies are conducted on a nonlinear diffusion-reaction process and a temperature cooling fin of high-speed aerospace vehicle, and the achieved results demonstrate the effectiveness of the developed control method.