5525123
FIX: feature-based indexing technique for XML documents
Indexing large XML databases is crucial for efficient evaluation of XML twig queries. In this paper, we propose a feature-based indexing technique, called FIX, based on spectral graph theory. The basic idea is that for each twig pattern in a collection of XML documents, we calculate a vector of features based on its structural properties. These features are used as keys for the patterns and stored in a B+tree. Given an XPath query, its feature vector is first calculated and looked up in the index. Then a further refinement phase is performed to fetch the final results. We experimentally study the indexing technique over both synthetic and real data sets. Our experiments show that FIX provides great pruning power and could gain an order of magnitude performance improvement for many XPath queries over existing evaluation techniques.
35884730
Compact access control labeling for efficient secure XML query evaluation
Fine-grained access controls for XML define access privileges at the granularity of individual XML nodes. In this paper, we present a fine-grained access control mechanism for XML data. This mechanism exploits the structural locality of access rights as well as correlations among the access rights of different users to produce a compact physical encoding of the access control data. This encoding can be constructed using a single pass over a labeled XML database. It is block-oriented and suitable for use in secondary storage. We show how this access control mechanism can be integrated with a next-of-kin (NoK) XML query processor to provide efficient, secure query evaluation. The key idea is that the structural information of the nodes and their encoded access controls are stored together, allowing the access privileges to be checked efficiently. Our evaluation shows that the access control mechanism introduces little overhead into the query evaluation process.
15488270
Segmentation of Spectrum Map for HFSWR Based on Feature Extraction
When targets fall in different types of clutter and noise background in High Frequency Surface Wave Radar (HFSWR), uniform detection algorithms always result in poor detection and tracking performances. To solve the problem, two methods are proposed in this paper by extracting the background features according to the probability distribution and the image characteristic of the spectrum map. The first method uses Parzen window for estimating probability density function and Kullback-Leibler convergence for evaluating the difference between the Azimuth-Range-Doppler cells in spectrum map which can be used to distinguish the homogenous detection background from the non-homogenous. The second method is proposed based on the image edge feature in multi-scale space. The real data results about HFSWR show that the proposed methods can not only identify noise/clutter but also help choose appropriate detection/tracking algorithms to improve performances in such complex environments.
2987811
Achieving fine-grained access control in virtual organizations
In a virtual organization environment, where services and data are provided and shared among organizations from different administrative domains and protected with dissimilar security policies and measures, there is a need for a flexible authentication framework that supports the use of various authentication methods and tokens. The authentication strengths derived from the authentication methods and tokens should be incorporated into an access-control decision-making process, so that more sensitive resources are available only to users authenticated with stronger methods. This paper reports our ongoing efforts in designing and implementing such a framework to facilitate multi-level and multi-factor adaptive authentication and authentication strength linked fine-grained access control. The proof-of-concept prototype is designed and implemented in the Shibboleth and PERMIS infrastructures, which specifies protocols to federate authentication and authorization information and provides a policy-driven, role-based, access-control decision-making capability. Copyright (c) 2006 John Wiley & Sons, Ltd.
14654466
A Purpose-Based Access Control Model
Achieving privacy preservation in a data-sharing computing environment is a challenging problem. The requirements for a privacy preserving data access policy should be formally specified in order to be able to establish consistency between the privacy policy and its purported implementation in practice. Previous work has shown that when specifying a privacy policy, the notion of purpose should be used as the basis for access control. A privacy policy should ensure that data can only be used for its intended purpose, and the access purpose should be compliant with the data's intended purpose. This paper presents a mechanism to specify privacy policy using VDM. The entities in the purpose-based access control model are specified, the invariants corresponding to the privacy requirements in privacy policy are specified, and the operations in the model and their proof obligations are defined and investigated.
1934229
Automated regression testing using DBT and Sleuth
SUMMARY Regression testing is an important activity in software maintenance. Current regression testing strategies can be categorized into two groups: retest all and selective regression testing. Each of these two groups encompasses a variety of strategies. In industrial practice, regression testing procedures vary widely. Sometimes, several regression testing techniques are used in combination. Technique selection is also innuenced by the expected quality of the system to be tested. Such variations in regression testing strategies and techniques mandate exibility for a regression testing tool. This paper presents regression testing support for Sleuth, a test generation tool based on Domain-Based Testing. We explain the rules for building regression tests for a variety of possible regression testing strategies from retest all strategies to selective regression testing strategies.
32437026
Fuzzy Comprehensive Evaluation for Power Network Operating Schemes
Based on the analytic hierarchy process, a fuzzy comprehensive evaluation method is proposed for power network operating schemes. Performance indices and corresponding membership functions are presented to denote their contributions on overall objective. The analytic hierarchy process is used to analyze influencing factors, to establish a hierarchical model and to rank the influencing factors in order of importance. After detailed analyses and calculations for each operating scheme, quantitative evaluation results that considering various factors comprehensively are obtained by a two-level fuzzy comprehensive evaluation. A decision support system using the proposed method is developed. Simulation results of a practical power system show its validity and effectiveness.