9772845
Performance Measurements for Privacy Preserving Data Mining
This paper establishes the foundation for the performance measurements of privacy preserving data mining techniques. The performance is measured in terms of the accuracy of data mining results and the privacy protection of sensitive data. On the accuracy side, we address the problem of previous measures and propose a new measure, named “effective sample size”, to solve this problem. We show that our new measure can be bounded without any knowledge of the data being mined, and discuss when the bound can be met. On the privacy protection side, we identify a tacit assumption made by previous measures and show that the assumption is unrealistic in many situations. To solve the problem, we introduce a game theoretic framework for the measurement of privacy.
5242879
Interactive rind modeling
In this paper, we describe a technique, with roots in topological graph theory, that we call rind modeling. It provides for the easy creation of surfaces resembling peeled and punctured rinds. We show how the method's two main steps of: 1) creation of a shell or crust like the rind of an orange, and 2) opening holes in the crust by punching or peeling can be encapsulated into a real time semi-automatic interactive algorithm. We include a number of worked examples, some by students in a first modeling course, that demonstrate the ease with which a large variety of intricate rind shapes can be created.
1021255
A minimal and complete set of operators for the development of robust manifold mesh modelers
In this paper, we identify a minimal and complete set of fundamental operators, which is necessary and sufficient for performing all homeomorphic and topological operations on 2- manifold mesh structures. Efficient algorithms are developed for the implementation of these operators. We also developed a set of powerful, user-friendly, and effective operators at the level of user-interface. Using these operators, we have developed a prototype system for robust, interactive, and user-friendly modeling of orientable 2-manifold meshes. Users of our system can perform a large set of homeomorphic and topological changes with these user-interface level operators. Our system is topologically robust in the sense that users will never create invalid 2-manifold mesh structure with these operators. In our system, the homeomorphic and topological surgery operations can be applied alternatively on 2-manifold meshes. With our system, users can blend surfaces, construct rinds, and open holes on these rind shapes. With our system, the shapes that look like solid, non-manifold, or 2-manifold with boundary can be manipulated. The system also provides automatic texture mapping during topology changes.
2261180
Graph Ear Decompositions and Graph Embeddings
Ear decomposition of a graph has been extensively studied in relation to graph connectivity. In this paper, a connection of ear decomposition to graph embeddings is exhibited. It is shown that constructing a maximum-paired ear decomposition of a graph and constructing a maximum-genus embedding of the graph are polynomial-time equivalent. Applications of this connection are discussed.
16331940
Optimal Parallel Routing in Star Networks
Star networks have recently been proposed as attractive alternatives to the popular hypercube for interconnecting processors on a parallel computer. In this paper, we present an efficient algorithm that constructs an optimal parallel routing in star networks. Our result improves previous results for the problem.
31382426
Strong Fault-Tolerance: Parallel Routing in Networks with Faults
A d-regular network G is strongly fault-tolerant if for any copy Gf of G with at most d - 2 faulty nodes, every pair of nonfaulty nodes u and v in Gf admits min{df(u), df (v)} node-disjoint paths in Gf from u to v, where df(u) and df(v) are the degrees of the nodes u and v in Gf. We show that popular network structures, such as hypercube and star networks, are strongly fault-tolerant. We develop efficient algorithms that construct the maximum number of node-disjoint paths of optimal or nearly optimal length in these networks with faulty nodes. Our algorithms are optimal in terms of their running time.
417259
Sample size for gene expression microarray experiments
MOTIVATION
Microarray experiments often involve hundreds or thousands of genes. In a typical experiment, only a fraction of genes are expected to be differentially expressed; in addition, the measured intensities among different genes may be correlated. Depending on the experimental objectives, sample size calculations can be based on one of the three specified measures: sensitivity, true discovery and accuracy rates. The sample size problem is formulated as: the number of arrays needed in order to achieve the desired fraction of the specified measure at the desired family-wise power at the given type I error and (standardized) effect size.


RESULTS
We present a general approach for estimating sample size under independent and equally correlated models using binomial and beta-binomial models, respectively. The sample sizes needed for a two-sample z-test are computed; the computed theoretical numbers agree well with the Monte Carlo simulation results. But, under more general correlation structures, the beta-binomial model can underestimate the needed samples by about 1-5 arrays.


CONTACT
jchen@nctr.fda.gov.
987186
Implementing Minimized Multivariate PKC on Low-Resource Embedded Systems
Multivariate (or $\mathcal{MQ}$) public-key cryptosystems (PKC) are alternatives to traditional PKCs based on large algebraic structures (e.g., RSA and ECC); they usually execute much faster than traditional PKCs on the same hardware. However, one major challenge in implementing multivariates in embedded systems is that the key size can be prohibitively large for applications with stringent resource constraints such as low-cost smart cards, sensor networks (e.g., Berkeley motes), and radio-frequency identification (RFID). In this paper, we investigate strategies for shortening the key of a multivariate PKC. We apply these strategies to the Tame Transformation Signatures (TTS) as an example and quantify the improvement in key size and running speed, both theoretically and via implementation. We also investigate ways to save die space and energy consumption in hardware, reporting on our ASIC implementation of TTS on a TSMC 0.25μm process. Even without any key shortening, the current consumption of TTS is only 21 μA for computing a signature, using 22,000 gate equivalents and 16,000 100-kHz cycles (160 ms). With circulant-matrix key shortening, the numbers go down to 17,000 gates and 4,400 cycles (44 ms). We therefore conclude: besides representing a future-proofing investment against the emerging quantum computers, multivariates can be immediately useful in niches.
18417913
IT induction in the food service industry
As part of the business strategy in a competitive environment, for an organization to induct information technology (IT) appropriately, business process reengineering (BPR) must be conducted. We propose a process that incorporates both management information systems and strategic management concepts for the IT induction. First, we develop a business competition strategy based on Porter’s five competitive forces; second, using concepts developed in the field of information systems the business processes are reengineered to improve effectiveness and efficiency; and finally, IT strategy is developed to achieve these goals. A real‐life case in the food service industry is used to illustrate this process.
7817604
Topological-based classification using artificial gene networks
The topological properties of artificial gene networks that rely on the assessment of similarities between the expressions profile of gene pairs would be consistent with specific cellular states. Furthermore, some topological properties of the network would have significant variance regarding different cellular states. In this study, we proposed a novel and highly efficient computational framework for a topological-based classification using microarray gene expression data. Owing to the high prediction accuracy with this approach, we believe that there is a noticeable advantage of using topological-based classification. We used the microarray gene expression data sets containing 14 classes of cancer to construct 14 basic artificial gene networks accordingly. For each test sample, we add the sample into the data set of each class and reconstruct all of the networks. Cancer type was classified according to the correlation of topological quantity between the basic artificial gene networks and the reconstructed networks. Total classification accuracy can achieve 78.26% in the test data set (95.83% in the standard data set). After screening the quality of the standard data set, we can achieve a prediction accuracy of 86.48% in the test data set. Thus, we can achieve higher prediction accuracy in comparison to previous studies.
2426986
Quantifying Privacy Leakage through Answering Database Queries
We assume a database consists of records of individuals with private or sensitive fields. Queries on the distribution of a sensitive field within a selected population in the database can be submitted to the data center. The answers to the queries leak private information of individuals though no identification information is provided. Inspired by decision theory, we present a quantitative model for the privacy protection problem in such a database query or linkage environment in this paper. In the model, the value of information is estimated from the viewpoint of the querier.To estimate the value, we define the information state of the data user by a class of probability distributions on the set of possible confidential values. We further define the usefulness of information based on how easy the data user can locate individuals that fit the description given in the queries. These states and the usefulness of information can be modified and refined by the user's knowledge acquisition actions. The value of information is then defined as the expected gain of the privacy receiver and the privacy is protected by imposing costs on the answers of the queries for balancing the gain.