1690622
Aggregate Query Answering on Anonymized Tables
Privacy is a serious concern when microdata need to be released for ad hoc analyses. The privacy goals of existing privacy protection approaches (e.g., k-anonymity and l-diversity) are suitable only for categorical sensitive attributes. Since applying them directly to numerical sensitive attributes (e.g., salary) may result in undesirable information leakage, we propose privacy goals to better capture the need of privacy protection for numerical sensitive attributes. Complementing the desire for privacy is the need to support ad hoc aggregate analyses over microdata. Existing generalization-based anonymization approaches cannot answer aggregate queries with reasonable accuracy. We present a general framework of permutation-based anonymization to support accurate answering of aggregate queries and show that, for the same grouping, permutation-based techniques can always answer aggregate queries more accurately than generalization-based approaches. We further propose several criteria to optimize permutations for accurate answering of aggregate queries, and develop efficient algorithms for each criterion.
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.
16108037
Jet subdivision schemes on the k-regular complex
We introduce a new family of subdivision schemes called jet subdivision schemes. Jet subdivision schemes are a natural generalization of the commonly used subdivision schemes for free-form surface modeling. In an order r jet subdivision scheme, rth order Taylor expansions, or r-jets, of functions are the essential objects being generated in a coarse-to-fine fashion. Standard subdivision surface methods correspond to the case r=0. Just as the standard free-form subdivision surface schemes, jet subdivision schemes are based on combining (i) a symmetric subdivision scheme in the shift-invariant setting with (ii) an extraordinary vertex rule. We formulate the notions of stationarity, symmetry, and smoothness for jet subdivision schemes. We then extend some well-known results in the theory of subdivision surfaces to the setting of jet subdivision schemes.By incorporating high order data into the subdivision rules, jet subdivision schemes offer more degrees of freedom for the design of extraordinary vertex rules than do standard subdivision schemes. Using a simple 2-point stencil, we construct an order 1 jet subdivision scheme, which is interpolatory, C1 everywhere, and free from polar artifacts at extraordinary vertices of any valence. It is similar to the popular butterfly scheme, but unlike the butterfly scheme, it produces surfaces that can be explicitly parameterized by spline functions. In addition, our jet subdivision scheme allows for explicit control of gradient information on the resulting surface.We address the problem of constructing curvature continuous subdivision schemes at extraordinary vertices by giving an example of a 'flexible C2 scheme' for extraordinary vertex of valence k = 3. The stencils for this subdivision scheme coincide with those of the popular Loop scheme. We discuss the mathematical structure of this example of a C2 scheme.
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.
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.
17323363
The Design of QoS Broker Algorithms for QoS-Capable Web Services
QoS (quality of service) support in Web services is an important issue since it ensures service usability and utility for each client and, in addition, improves server utilization. In this article, we present a QoS-capable Web service architecture, QCWS, by introducing a QoS broker module between service clients and providers (servers). 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 study two resource allocation algorithms (HQ and RQ) used by QoS brokers acting as the front-end of servers. The goals of the algorithms are to maximize the server resource usage while minimizing the QoS instability for each client. The first algorithm, HQ, assigns a homogeneous service level to all clients on the system and adjusts the service level according to the number of active clients. The second algorithm, RQ, assigns different service levels to clients according to their needs. Both algorithms try to minimize the resource reallocations for existing clients. The QoS performance and instability trade-offs are studied by simulation.
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