Behavioral Attestation for Web Services using access policies

Service Oriented Architecture with underlying technologies like web services and web service orchestration opens new vistas for integration among business processes operating in heterogeneous environments. However, such dynamic collaborations require a highly secure environment at each respective business partner site. Existing web services standards address the issue of security only on the service provider platform. The partner platforms to which sensitive information is released have till now been neglected. Remote Attestation is a relatively new field of research which enables an authorized party to verify that a trusted environment actually exists on a partner platform. To incorporate this novel concept in to the web services realm, a new mechanism called WS-Attestation has been proposed. This mechanism provides a structural paradigm upon which more fine-grained solutions can be built. In this paper, we present a novel framework, Behavioral Attestation for Web Services, in which XACML is built on top of WS-Attestation in order to enable more flexible remote attestation at the web services level. We propose a new type of XACML policy called XACML behavior policy, which defines the expected behavior of a partner platform. Existing web service standards are used to incorporate remote attestation at the web services level and a prototype is presented, which implements XACML behavior policy using low-level attestation techniques.     

Understanding post‐adoption IS usage stages: an empirical assessment of self‐service information systems

Organisations have invested in self‐service information systems (IS) to provide a direct interface for service delivery. Enriching the usage of these systems can provide organisations with immense benefits. However, limited research has been directed towards understanding post‐adoption IS usage behaviour in general and specifically in the context of self‐service IS. This study proposes post‐adoption IS usage behaviour as a broader concept constituting feature level usage of IS, integration of IS in the work system and exploration of new uses of IS. We evaluate how the new conceptualisation can be used to classify users at different stages of self‐service IS usage. Further, we examine user perceptions that differentiate among the users situated at different self‐service IS usage stages. Data were collected in the context of a self‐service Web‐based IS to validate the post‐adoption IS usage constructs and to examine the proposed thesis. The newly developed conceptual structure and measures for post‐adoption IS usage behaviour exhibit strong psychometric properties. The analysis shows three distinct post‐adoption IS usage stages and highlights that usefulness, user‐initiated learning, ease of use, satisfaction and voluntariness of use differentiate users at the different stages of post‐adoption IS usage. The results show that these variables aggregate into value confirmation and learning orientation as two higher‐level concepts. Further, we evaluate the predictive efficacy of the research model in classifying users into different post‐adoption self‐service IS usage stages. Implications are drawn for future research.     

A model-based survey of alert correlation techniques

As telecommunication networks evolve rapidly in terms of scalability, complexity, and heterogeneity, the efficiency of fault localization procedures and the accuracy in the detection of anomalous behaviors are becoming important factors that largely influence the decision making process in large management companies. For this reason, telecommunication companies are doing a big effort investing in new technologies and projects aimed at finding efficient management solutions. One of the challenging issues for network and system management operators is that of dealing with the huge amount of alerts generated by the managed systems and networks. In order to discover anomalous behaviors and speed up fault localization processes, alert correlation is one of the most popular resources. Although many different alert correlation techniques have been investigated, it is still an active research field. In this paper, a survey of the state of the art in alert correlation techniques is presented. Unlike other authors, we consider that the correlation process is a common problem for different fields in the industry. Thus, we focus on showing the broad influence of this problem. Additionally, we suggest an alert correlation architecture capable of modeling current and prospective proposals. Finally, we also review some of the most important commercial products currently available.     

MC-MLAS: Multi-channel Minimum Latency Aggregation Scheduling in Wireless Sensor Networks

Data aggregation is a key, yet time-consuming functionality in wireless sensor networks (WSNs). Multi-channel design is a promising technique to alleviate interference as a primary reason for long latency of TDMA aggregation scheduling. Indeed, it provides more potential of parallel transmissions over different frequency channels, thus minimizing time latency. In this paper, we focus on designing a multi-channel minimum latency aggregation scheduling protocol, named MC-MLAS, using a new joint approach for tree construction, channel assignment, and transmission scheduling. To our best knowledge, this is the first work in the literature which combines orthogonal channels and partially overlapping channels to consider the total latency involved in data aggregation. Extensive simulations verify the superiority of MC-MLAS in WSNs.     

An extended divide-and-conquer algorithm for a generalized class of multibody constraints

An extension to the divide-and-conquer algorithm (DCA) is presented in this paper to model constrained multibody systems. The constraints of interest are those applied to the system due to the inverse dynamics or control laws rather than the kinematically closed loops which have been studied in the literature. These imposed constraints are often expressed in terms of the generalized coordinates and speeds. A set of unknown generalized constraint forces must be considered in the equations of motion to enforce these algebraic constraints. In this paper dynamics of this class of multibody constrained systems is formulated using a Generalized-DCA. In this scheme, introducing dynamically equivalent forcing systems, each generalized constraint force is replaced by its dynamically equivalent spatial constraint force applied from the appropriate parent body to the associated child body at the connecting joint without violating the dynamics of the original system. The handle equations of motion are then formulated considering these dynamically equivalent spatial constraint forces. These equations in the GDCA scheme are used in the assembly and disassembly processes to solve for the states of the system, as well as the generalized constraint forces and/or Lagrange multipliers.     

Modeling and robust discrete LQ repetitive control of electrically driven robots

Discrete linear quadratic control has been efciently applied to linear systems as an optimal control.However,a robotic system is highly nonlinear,heavily coupled and uncertain.To overcome the problem,the robotic system can be modeled as a linear discrete-time time-varying system in performing repetitive tasks.This modeling motivates us to develop an optimal repetitive control.The contribution of this paper is twofold.For the frst time,it presents discrete linear quadratic repetitive control for electrically driven robots using the mentioned model.The proposed control approach is based on the voltage control strategy.Second,uncertainty is efectively compensated by employing a robust time-delay controller.The uncertainty can include parametric uncertainty,unmodeled dynamics and external disturbances.To highlight its ability in overcoming the uncertainty,the dynamic equation of an articulated robot is introduced and used for the simulation,modeling and control purposes.Stability analysis verifes the proposed control approach and simulation results show its efectiveness.     

Adiabatic quantum optimization with qudits

Most realistic solid state devices considered as qubits are not true two-state systems. If the energy separation of the upper energy levels from the lowest two levels is not large, then these upper states may affect the evolution of the ground state over time and therefore cannot be neglected. In this work, we study the effect of energy levels beyond the lowest two energy levels on adiabatic quantum optimization in a device with a double-well potential as the basic logical element. We show that the extra levels can be modeled by adding additional ancilla qubits coupled to the original logical qubits, and that the presence of upper levels has no effect on the final ground state. We also study the influence of upper energy levels on the minimum gap for a set of 8-qubit spin glass instances.     

Comparative evaluation of text classification techniques using a large diverse Arabic dataset

A vast amount of valuable human knowledge is recorded in documents. The rapid growth in the number of machine-readable documents for public or private access necessitates the use of automatic text classification. While a lot of effort has been put into Western languages—mostly English—minimal experimentation has been done with Arabic. This paper presents, first, an up-to-date review of the work done in the field of Arabic text classification and, second, a large and diverse dataset that can be used for benchmarking Arabic text classification algorithms. The different techniques derived from the literature review are illustrated by their application to the proposed dataset. The results of various feature selections, weighting methods, and classification algorithms show, on average, the superiority of support vector machine, followed by the decision tree algorithm (C4.5) and Naïve Bayes. The best classification accuracy was 97 % for the Islamic Topics dataset, and the least accurate was 61 % for the Arabic Poems dataset.     

Human eye sclera detection and tracking using a modified time-adaptive self-organizing map

This paper investigates the use of time-adaptive self-organizing map (TASOM)-based active contour models (ACMs) for detecting the boundaries of the human eye sclera and tracking its movements in a sequence of images. The task begins with extracting the head boundary based on a skin-color model. Then the eye strip is located with an acceptable accuracy using a morphological method. Eye features such as the iris center or eye corners are detected through the iris edge information. TASOM-based ACM is used to extract the inner boundary of the eye. Finally, by tracking the changes in the neighborhood characteristics of the eye-boundary estimating neurons, the eyes are tracked effectively. The original TASOM algorithm is found to have some weaknesses in this application. These include formation of undesired twists in the neuron chain and holes in the boundary, lengthy chain of neurons, and low speed of the algorithm. These weaknesses are overcome by introducing a new method for finding the winning neuron, a new definition for unused neurons, and a new method of feature selection and application to the network. Experimental results show a very good performance for the proposed method in general and a better performance than that of the gradient vector field (GVF) snake-based method.