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
1675549
QCWS: an implementation of QoS-capable multimedia web services
QoS (Quality of Service), which defines service quality such as latency, availability, timeliness and reliability, is important for web applications that provide real-time information, multimedia content, or time-critical services. Many web applications are best implemented by servers with a guaranteed server processing capacity. In this research, we study the QoS control issues using the current Web services standards. We propose a QoS-capable Web service architecture, QCWS, by deploying a QoS broker between Web service clients and providers. The functions of the QoS broker module include tracking QoS information about servers, making selection decisions for clients, and negotiating with servers to get QoS agreements. We have implemented a QCWS prototype using IBM WSDK, enhanced with simple QoS capabilities. We have measured the performance running under different service priorities.
16639374
An identifiability-based access control model for privacy protection in open systems
We argue that in open systems one's private information disclosure needs to be dynamically controlled based on both its sensitivity and the possibility that a user's identity is revealed. Then we propose an identifiability-based access control scheme, which not only properly control usrers' private information, but also increase users' access to web services.
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.
14639870
Tracking articulated body by dynamic Markov network
A new method for visual tracking of articulated objects is presented. Analyzing articulated motion is challenging because the dimensionality increase potentially demands tremendous increase of computation. To ease this problem, we propose an approach that analyzes subparts locally while reinforcing the structural constraints at the mean time. The computational model of the proposed approach is based on a dynamic Markov network, a generative model which characterizes the dynamics and the image observations of each individual subpart as well as the motion constraints among different subparts. Probabilistic variational analysis of the model reveals a mean field approximation to the posterior densities of each subparts given visual evidence, and provides a computationally efficient way for such a difficult Bayesian inference problem. In addition, we design mean field Monte Carlo (MFMC) algorithms, in which a set of low dimensional particle filters interact with each other and solve the high dimensional problem collaboratively. Extensive experiments on tracking human body parts demonstrate the effectiveness, significance and computational efficiency of the proposed method.
18018686
Limiting the Disclosure of Access Control Policies during Automated Trust Negotiation
Automated trust negotiation is a new approach to establishing trust between strangers through the exchange of property-based digital credentials, and the use of mobile access control policies that specify what combinations of credentials a stranger must supply in order to gain access to each local service or credential. In this paper, we show that access control policies can also contain sensitive information that should be protected from inappropriate access by strangers during negotiation. We present and analyze two automated trust negotiation strategies that support protection for access control policies. The first is the relevant credentials set strategy, which does not directly disclose access control policies and has a fast running time, but may disclose more credentials than strictly necessary. The second strategy is the all relevant policies strategy, which freely discloses all relevant access control policies that the other negotiating party has earned access to during negotiation, and offers the possibility of disclosing fewer credentials
8787255
Approximate XML joins
XML is widely recognized as the data interchange standard for tomorrow, because of its ability to represent data from a wide variety sources. Hence, XML is likely to be the format through which data from multiple sources is integrated.In this paper we study the problem of integrating XML data sources through correlations realized as join operations. A challenging aspect of this operation is the XML document structure. Two documents might convey approximately or exactly the same information but may be quite different in structure. Consequently approximate match in structure, in addition to, content has to be folded in the join operation. We quantify approximate match in structure and content using well defined notions of distance. For structure, we propose computationally inexpensive lower and upper bounds for the tree edit distance metric between two trees. We then show how the tree edit distance, and other metrics that quantify distance between trees, can be incorporated in a join framework. We introduce the notion of reference sets to facilitate this operation. Intuitively, a reference set consists of data elements used to project the data space. We characterize what constitutes a good choice of a reference set and we propose sampling based algorithms to identify them. This gives rise to a variety of algorithmic approaches for the problem, which we formulate and analyze. We demonstrate the practical utility of our solutions using large collections of real and synthetic XML data sets.