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.
268452
Query planning with limited source capabilities
In information-integration systems, sources may have diverse and limited query capabilities. We show that because sources have restrictions on retrieving their information, sources not mentioned in a query can contribute to the query result by providing useful bindings. In some cases we can access sources repeatedly to retrieve bindings to answer a query, and query planning thus becomes considerably more challenging. We find all the obtainable answers to a query by translating the query and source descriptions to a simple recursive Datalog program, and evaluating the program on the source relations. This program often accesses sources that are not in the query. Some of these accesses are essential, as they provide bindings that let us query sources, which we could not do otherwise. However, some of these accesses can be proven not to add anything to the query's answer. We show in which cases these off-query accesses are useless, and prove that in these cases we can compute the complete answer to the query by using only the sources in the query. In the cases where off-query accesses are necessary, we propose an algorithm for finding all the useful sources for a query. We thus solve the optimization problem of eliminating the unnecessary source accesses, and optimize the program to answer the query.
3403058
Selectivity Estimation for Fuzzy String Predicates in Large Data Sets
Many database applications have the emerging need to support fuzzy queries that ask for strings that are similar to a given string, such as "name similar to smith" and "telephone number similar to 412-0964." Query optimization needs the selectivity of such a fuzzy predicate, i.e., the fraction of records in the database that satisfy the condition. In this paper, we study the problem of estimating selectivities of fuzzy string predicates. We develop a novel technique, called SEPIA, to solve the problem. It groups strings into clusters, builds a histogram structure for each cluster, and constructs a global histogram for the database. It is based on the following intuition: given a query string q, a preselected string p in a cluster, and a string s in the cluster, based on the proximity between q and p, and the proximity between p and s, we can obtain a probability distribution from a global histogram about the similarity between q and s. We give a full specification of the technique using the edit distance function. We study challenges in adopting this technique, including how to construct the histogram structures, how to use them to do selectivity estimation, and how to alleviate the effect of non-uniform errors in the estimation. We discuss how to extend the techniques to other similarity functions. Our extensive experiments on real data sets show that this technique can accurately estimate selectivities of fuzzy string predicates.
11931665
Clustering for Approximate Similarity Search in High-Dimensional Spaces
We present a clustering and indexing paradigm (called Clindex) for high-dimensional search spaces. The scheme is designed for approximate similarity searches, where one would like to find many of the data points near a target point, but where one can tolerate missing a few near points. For such searches, our scheme can find near points with high recall in very few IOs and perform significantly better than other approaches. Our scheme is based on finding clusters and, then, building a simple but efficient index for them. We analyze the trade-offs involved in clustering and building such an index structure, and present extensive experimental results.
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.
81526
Capability based mediation in TSIMMIS
Conventional mediators focus their attention on the contents of the sources and their relationship to the integrated views provided to the users. They do not take into account the capabilities of sources to answer queries. This may lead them to generate plans involving source queries that cannot be answered by the sources. In the TSIMMIS system, we have developed a source capability sensitive plan generation module that constructs feasible plans for user queries in the presence of limited source capabilities
35008704
Image segmentation based on a multiresolution Bayesian framework
A multiresolution Markov random field (MMRF) approach to texture segmentation which makes use of both regional and boundary information is proposed in this work. The algorithm is designed to improve the efficiency and solve two problems: over-segmentation and under-segmentation. At each resolution level, regional information and boundary information between textured regions is extracted to describe each block using the multiresolution Fourier transform (MFT). The image is then modelled as a sequence of Markov random fields (MRFs) of varying resolution and a Gibbs sampling scheme is applied to label the constituent sites at each scale by seeking the configuration with minimal interaction energy. The interaction energy is defined as a function of the regional and boundary information. The constraints of region context, and boundary smoothness and connectivity are also encoded in the interaction energy. Once the algorithm converges at a given scale, the segmentation result is propagated down to the next resolution for further refinement.
15126663
Semi-fragile watermarking scheme for authentication of JPEG images
With the increasing popularity of JPEG images, a need arises to devise effective watermarking techniques which consider JPEG compression as an acceptable manipulation. In this paper, we present a semi-fragile watermarking scheme which embeds a watermark in the quantized DCT domain. It is tolerant to JPEG compression to a pre-determined lowest quality factor, but is sensitive to all other malicious attacks, either in spatial or transform domains. Feature codes are extracted based on the relative sign and magnitudes of coefficients, and these are invariant due to an important property of JPEG compression. The employment of a nine-neighborhood mechanism ensures that non-deterministic block-wise dependence is achieved. Analysis and experimental results are provided to support the effectiveness of the scheme.
18972651
User preferences, information transactions and location-based services: A study of urban pedestrian wayfinding
Though research into location-based services (LBS) is being carried out across a number of disciplines, user aspects of LBS remains a cross-cutting theme. In this paper, the research focuses on investigating the user information requirements from LBS at individual level, with emphasis on the interactive nature of information transactions between environments, individuals and mobile devices. Based on a proposed conceptual model, urban pedestrian wayfinding experiments have been implemented in an immersive virtual reality test environment. Automated and semi-automated methods of data collection have allowed an integrated picture of participant behaviour and information preferences to be constructed and analysed. The results of this study show that there are clear user preferences in information requirements in completing wayfinding tasks. However, changes in user preferences during the wayfinding tasks do occur in response to levels of confidence, different spatial layouts and the wayfinding situations individuals encounter. The outcomes indicate that the proposed conceptual interaction model and adopted implementation approach assist in understanding user behaviour and information preferences for LBS.
15797731
A Novel Indexing Approach for Efficient and Fast Similarity Search of Captured Motions
Indexing of motion data is important for quickly searching similar motions for sign language recognition and gait analysis and rehabilitation. This paper proposes a simple and efficient tree structure for indexing motion data with dozens of attributes. Feature vectors are extracted for indexing by using singular value decomposition (SVD) properties of motion data matrices. By having similar motions with large variations indexed together, searching for similar motions of a query needs only one node traversal at each tree level, and only one feature needs to be considered at one tree level. Experiments show that the majority of irrelevant motions can be pruned while retrieving all similar motions, and one traversal of the indexing tree takes only several microseconds with the existence of motion variations.
29013572
Semi-supervised Learning in Medical Image Database
This paper presents a novel graph-based algorithm for solving the semi-supervised learning problem. The graph-based algorithm makes use of the recent advances in stochastic graph sampling technqiue and a modeling of the labeling consistency in semi-supervised learning. The quality of the algorithm is empirically evaluated on a synthetic clustering problem. The semi-supervised clustering is also applied to the problem of symptoms classification in medical image database and shows promising results.