14568428
A reputation and trust management broker framework for Web applications
This paper presents a distributed reputation and trust management framework that addresses the challenges of eliciting, evaluating and propagating reputation for Web applications. We propose a broker framework where every service user is associated with a broker who may represent multiple users. A broker collects for its users the distributed reputation ratings about any Web service. In return, a user provides its broker the transaction rating after every transaction with any service in order to build up the reputation database on all services. In addition, brokers form a trust network where they exchange and collect reputation data about services. By delegating trust management to brokers, individual users only need to ask their brokers about the reputation of a service before any transaction with a server. The only overhead for a user is the responsibility to share the reputation feedback with its broker. We present the distributed reputation and trust management framework and show the performance of the system by simulations.
7315404
Service selection algorithms for Web services with end-to-end QoS constraints
Web services are new forms of Internet software that can be universally deployed and invoked using standard protocols. Services from different providers can be integrated into a composite service regardless of their locations, platforms, and/or execution speeds to implement complex business processes and transactions. In this paper, we study the end-to-end QoS issues of composite services by utilizing a QoS broker that is responsible for selecting and coordinating the individual service component. We design the service selection algorithms used by QoS brokers to construct the optimal composite service. The objective of the algorithms is to maximize the user-defined utility function value while meeting the end-to-end delay constraint. We propose two solution approaches to the service selection problem: the combinatorial approach, by modeling the problem as the Multiple Choice Knapsack Problem (MCKP), and the graph approach, by modeling the problem as the constrained shortest path problem in the graph theory. We study efficient solutions for each approach.
46251955
Service Selection Algorithms for Web Services with End-to-End QoS Constraints
Web services are new forms of Internet software that can be universally deployed and invoked using standard protocol. Services from different providers can be integrated to provide composite services. In this paper, we study the end-to-end QoS issues of composite service by utilizing a QoS broker that is responsible for coordinating the individual service component to meet the quality constraint. We design the service selection algorithms used by QoS brokers to meet end-to-end QoS constraints. The objective of the algorithms is to maximize the user-defined utility while meeting the end-to-end delay constraint. We model the problem as the multiple choice knapsack problem (MCKP) and provide efficient solutions. The algorithms are tested for their performance.
22470084
A broker-based framework for QoS-aware Web service composition
Web services are modular web applications that can be independently deployed and invoked by other software or services on the web. This offers enterprises the capability to integrate in-house business services with external Web services to conduct complex business transactions. The integration efficiency and flexibility are critical for services composition. For Web services providing a similar functionality, Quality of Service (QoS) is the main factor to differentiate them. The overall QoS of a business process must meet a user's requirement. In this paper, we propose a broker-based framework to facilitate dynamic integration and adaptation of QoS-aware Web services with end-to-end QoS constraints. The key functions of a dynamic broker include service collection, selection, composition and adaptation. Our study considers both functional and QoS characteristics of Web services to identify the optimal business process solutions.
31957917
Modeling and Measuring Privacy Risks in QoS Web Services
The privacy issue for QoS Web services is considered. As more Web services are constructed and deployed, many of our personal needs may be served by more than one service providers regardless of their platforms and implementation technologies. Service selection is performed by comparing the QoS attributes of all candidate services. Releasing private data without due control may raise the risk of allowing potential adversaries to collect, reveal or utilize one's data in undesirable ways. We propose a QoS model that quantifies a user's privacy risk in order to make the service selection process manageable. The privacy risk is derived using the percentage of the private data set to be released, and user-defined context-oriented weights that quantify the potential damage of privacy leaking in a specific context. We have included privacy risk cost as one of the QoS parameters by extending the end-to-end QoS composition algorithms developed previously
1794794
Service Selection Algorithms for Composing Complex Services with Multiple QoS Constraints
One of the promises of the service-oriented architecture (SOA) is that complex services can be composed using individual services. Individual services can be selected and integrated either statically or dynamically based on the service functionalities and performance constraints. For many distributed applications, the runtime performance (e.g. end-to-end delay, cost, reliability and availability) of complex services are very important. In our earlier work, we have studied the service selection problem for complex services with only one QoS constraint. This paper extends the service selection problem to multiple QoS constraints. The problem can be modelled in two ways: the combinatorial model and the graph model. The combinatorial model defines the problem as the multi-dimension multi-choice 0-1 knapsack problem (MMKP). The graph model defines the problem as the multi-constraint optimal path (MCOP) problem. We propose algorithms for both models and study their performances by test cases. We also compare the pros & cons between the two models.
14377828
Switching observation models for contour tracking in clutter
We propose a generative model approach to contour tracking against nonstationary clutter and to coping with occlusions by explicit modelling and inferring. The proposed dynamic Bayesian networks consist of multiple hidden processes, which model the target, the clutter and the occlusions. The image observation models, which depict the generation of the image features, are conditioned on all the hidden processes. Based on this framework, the tracker can automatically switch among different observation models according to the hidden states of the clutter and occlusions. In addition, the inference of these hidden states provides self-evaluations for the tracker. The tracking and inference are implemented based on sequence Monte Carlo techniques. The effectiveness of the proposed approach to robust tracking and inferring nonstationary clutter and occlusion is demonstrated for a variety of image sequences.
15013952
Policy migration for sensitive credentials in trust negotiation
Trust negotiation is an approach to establishing trust between strangers through the bilateral, iterative disclosure of digital credentials. Under automated trust negotiation, access control policies are associated with sensitive credentials to control under what circumstances those credentials can be disclosed. Ideally, the information in a user's sensitive credential should not be known by others unless the corresponding policy is satisfied. However, the original model for user interaction in trust negotiation has pitfalls which can be easily exploited to infer one's private information, even if access control policies are strictly enforced. To preserve one's privacy, a more flexible interaction model for trust negotiation is required. On the other hand, it is also desirable for two parties to be able to establish trust whenever possible. There is potentially a conflict between privacy preservation and the assurance of a successful trust negotiation. In this paper, we identify the situation where sensitive information can be inferred through observing one's behavior in trust negotiation. Then we propose policy migration as one approach to preventing such inference. Compared to previously proposed approaches, policy migration has a low management overhead, and provides a nice balance between inference prevention and guarantees of success in trust establishment. We also discuss the limitations of policy migration, and possible directions for more comprehensive solutions.
2218750
A Classification Scheme for Trust Functions in Reputation-Based Trust Management
Reputation is an important means to establish trust in decentralized environments such as the Semantic Web. In reputation-based trust management, an entity's reputation is usually built on feedback from those who have direct interactions with the entity. A trust function is used to infer one's trustworthiness based on such feedback. Many trust functions have been proposed in the literature. They are typically designed for specific application domains, thus differ in a variety of aspects, including trust inference methodologies, complexity and accuracy. In this paper, we propose a classification scheme for trust functions, which will help the systematic analysis and selection of trust functions for particular applications.
584843
Identifying Error-Prone Software&#8212;An Empirical Study
A major portion of the effort expended in developing commercial software today is associated with program testing. Schedule and/ or resource constraints frequently require that testing be conducted so as to uncover the greatest number of errors possible in the time allowed. In this paper we describe a study undertaken to assess the potential usefulness of various product-and process-related measures in identifying error-prone software. Our goal was to establish an empirical basis for the efficient utilization of limited testing resources using objective, measurable criteria. Through a detailed analysis of three software products and their error discovery histories, we have found simple metrics related to the amount of data and the structural complexity of programs to be of value for this purpose.
3138964
Defining and Measuring Policy Coverage in Testing Access Control Policies
To facilitate managing access control in a system, security officers increasingly write access control policies in specification languages such as XACML, and use a dedicated software component called a Policy Decision Point (PDP). To increase confidence on written policies, certain types of policy testing (often in an ad hoc way) are usually conducted, which probe the PDP with some typical requests and check PDP's responses against expected ones. This paper develops a first step toward systematic policy testing by defining and measuring policy coverage when testing policies. We have developed a coverage-measurement tool to measure policy coverage given a set of XACML policies and a set of requests. We have developed a tool for request generation, which randomly generates requests for a given set of policies, and a tool for request reduction, which greedily selects a nearly minimal set of requests for achieving the same coverage as the originally generated requests. To evaluate coverage-based request reduction and its effect on fault detection, we have conducted an experiment with mutation testing on a set of real policies. Our experimental results show that the coveragebased test reduction can substantially reduce the size of generated requests and incur only relatively low loss on fault detection. We also conduct a study on the policy coverage achieved by manually generated requests.