3090145
XGuard: a system for publishing XML documents without information leakage in the presence of data inference
In data publishing, if the data is published carelessly, public users could use common knowledge to infer more information from the published data, causing leakage of sensitive information. To address related research challenges, we develop a system called XGuard, which can help data owners publish a partial XML document without leaking sensitive information, even if public users can do inference. Specifically, the system has the following functionalities. i) It allows the data owner to define sensitive information and specify common knowledge as XML constraints. ii) Given a partial document, the system can validate if the document can cause information leakage due to common knowledge and how much data can be leaked. iii) The system can help the data owner interactively analyze the data inference and produce a secure valid partial document using the algorithms.
1386080
Using Constraints to Describe Source Contents in Data Integration Systems
In data integration systems, information sources often have constraints, such as "all houses stored at a source have a unique address." These constraints are useful in computing answers to queries and facilitating information exchange.
8510271
Supporting Efficient Record Linkage for Large Data Sets Using Mapping Techniques
This paper describes an efficient approach to record linkage. Given two lists of records, the record-linkage problem consists of determining all pairs that are similar to each other, where the overall similarity between two records is defined based on domain-specific similarities over individual attributes. The record-linkage problem arises naturally in the context of data cleansing that usually precedes data analysis and mining. Since the scalability issue of record linkage was addressed in [21], the repertoire of database techniques dealing with multidimensional data sets has significantly increased. Specifically, many effective and efficient approaches for distance-preserving transforms and similarity joins have been developed. Based on these advances, we explore a novel approach to record linkage. For each attribute of records, we first map values to a multidimensional Euclidean space that preserves domain-specific similarity. Many mapping algorithms can be applied, and we use the Fastmap approach [16] as an example. Given the merging rule that defines when two records are similar based on their attribute-level similarities, a set of attributes are chosen along which the merge will proceed. A multidimensional similarity join over the chosen attributes is used to find similar pairs of records. Our extensive experiments using real data sets show that our solution has very good efficiency and recall.
10902397
Protecting Individual Information Against Inference Attacks in Data Publishing
In many data-publishing applications, the data owner needs to protect sensitive information pertaining to individuals. Meanwhile, certain information is required to be published. The sensitive information could be considered as leaked, if an adversary can infer the real value of a sensitive entry with a high confidence. In this paper we study how to protect sensitive data when an adversary can do inference attacks using association rules derived from the data. We formulate the inference attack model, and develop complexity results on computing a safe partial table. We classify the general problem into subcases based on the requirements of publishing information, and propose the corresponding algorithms for finding a safe partial table to publish. We have conducted an empirical study to evaluate these algorithms on real data.
2113121
Computing capabilities of mediators
Existing data-integration systems based on the mediation architecture employ a variety of mechanisms to describe the query-processing capabilities of sources. However, these systems do not compute the capabilities of the mediators based on the capabilities of the sources they integrate. In this paper, we proposed a framework to capture a rich variety of query-processing capabilities of data sources and mediators. We present algorithms to compute the set of supported queries of a mediator, based on the capability limitations of its sources. Our algorithms take into consideration a variety of query-processing techniques employed by mediators to enhance the set of supported queries.
7967297
2D BubbleUp: Managing Parallel Disks for Media Servers
In this study we present a scheme called two-dimensional BubbleUp (2DB) for managing parallel disks in a multimedia server. Its goal is to reduce initial latency for interactive multimedia applications, while balancing disk loads to maintain high throughput. The 2DB scheme consists of a data placement and a request scheduling policy. The data placement policy replicates frequently accessed data and places them cyclically throughout the disks. The request scheduling policy attempts to maintain free ``service slots'''' in the immediate future. These slots can then be used to quickly service newly arrived requests. Through examples and simulation, we show that our scheme significantly reduces initial latency and maintains throughput comparable to that of the traditional schemes.
39703644
A new family of locally 5-arc transitive graphs
We present a new family of locally 5-arc transitive graphs. The graphs constructed are bipartite with valency {2^m+1,2^m}. The actions of the automorphism group on the two bipartite halves are distinctly different and the corresponding amalgams are new.
5657260
Guided Cluster Discovery with Markov Model
Cluster discovery is an essential part of many data mining applications. While cluster discovery process is mainly unsupervised in nature, it can often be aided by a small amount of labeled data. A probabilistic model on the clustering structure is adopted and a novel unified energy equation for clustering that incorporates both labeled data and unlabeled data is introduced. This formulation is inspired by a force-field model integrating labeling constraint on labeled data and similarity information on unlabeled data for joint estimation. Experimental results show that good clusters can be identified using small amount of labeled data.
34090759
Segmentation of external force field for automatic initialization and splitting of snakes
Active contours or snakes have been extensively utilized in handling image segmentation and classification problems. In traditional active contour models, snake initialization is performed manually by users, and topological changes, such as splitting of the snake, cannot be automatically handled. In this paper, we introduce a new method to solve the snake initialization and splitting problem, based on an area segmentation approach: the external force field is segmented first, and then the snake initialization and splitting can be automatically performed by using the segmented external force field. Such initialization and splitting produces multiple snakes, each of which is within the capture range associated to an object and will be evolved to the object boundary. The external force used in this paper is a gradient vector flow with an edge-preserving property (EPGVF), which can prevent the snakes from passing over weak boundaries. To segment the external force field, we represent it with a graph, and a graph-theory approach can be taken to determine the membership of each pixel. Experimental results establish the effectiveness of the proposed approach.
157891
ROLEX: relational on-line exchange with XML
1. OVERVIEW ROLEX is a research system for closely coupled XML-relational interoperation [2]. Whereas typical XML-based applications interoperate with existing relational databases via a “shred-and-publish” approach, the ROLEX system seeks to provide direct access to relational data via XML interfaces at the speed of cached XML data. To achieve this, ROLEX is integrated tightly with both the DBMS and the application through a standard interface supported by most XML parsers, the Document Object Model (DOM). Thus, in general, an application need not be modified to be used with ROLEX. With the DBMS providing performance qualitatively similar to cached data, XML applications can rely on it for concurrency control and recovery services. To support our integration model and performance goals, ROLEX is built on the DataBlitz Main-Memory Database System, allowing us to capitalize on low-latency access to data while still providing concurrency control and recovery [1]. The DOM interface supports the expected navigation functions: parent-to-child, child-to-parent, and sibling-to-sibling. A DOM interface to an XML view query supports all the DOM operations and behaves as if the user were navigating the XML document resulting from the query. In ROLEX, we implement a virtual DOM tree that goes a step further by providing the same interface without creating a physical DOM tree. A novelty of ROLEX is that it uses a navigational profile for the user or application when it optimizes view-query plans. While navigational profiles can, in principle, be quite complex, we currently adopt a very simple model. If n is a node in the schema tree with parent p, the navigation profile stores the probability that some node in the DOM tree generated by n will be visited given that its parent, generated by p, has been visited. Query output is produced by a navigable query plan. It provides, for each node n in the schema tree of a view query, two entities: (1) a subplan for evaluating the tag query for n, and (2) a navigation index. The navigation index serves to materialize the output of the tag query and supports efficient lookup based on parameter values,
40002746
Soft computing approach to feature extraction
Based on both wavelet theory and fuzzy theory, a soft computing system (SCS) is proposed for feature extraction of signals. The proposed SCS approach possesses the advantages of soft decision-making on wavelet coefficients for feature extraction, adaptive selectivity of mapping factors to coarse-to-fine resolution, and compact form of feature representation with the SCS feature-extractor. Fuzzy sets are used to provide a robust representation for signal information, and wavelet transform is used to decompose a signal into detail and approximation signals. At a given resolution, the detail and approximation signals are inputted to the proposed SCS to extract signal features at that resolution level. The sensitivity in feature extraction of the proposed approach can be adapted by tuning the fuzzy sets for the detail and approximation signals. At different resolutions, the signal can be examined and suitable features can be extracted. Examples of both one-dimensional signals and two-dimensional fingerprint images are used to illustrate the proposed soft computing approach for feature extraction and pattern recognition. The results show that the extracted features are sensitive enough to distinguish the similar signal from the different ones and are robust enough to tolerate noise corruption.