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Electronic Transactions
, 2007
"... mobile technologies, privacy, security, access control, database, ubiquitous computing, information management, services infrastructure Mobile companions such as smartphones and PDAs are very personal and carry a lot of sensitive data about their owners. With new services aimed at providing more tar ..."
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mobile technologies, privacy, security, access control, database, ubiquitous computing, information management, services infrastructure Mobile companions such as smartphones and PDAs are very personal and carry a lot of sensitive data about their owners. With new services aimed at providing more targeted information retrieval through increased interactions with these devices, privacy concerns of individuals must be addressed. Existing solutions give users little control over release of this information. MUPPET is a privacyaware information brokerage framework that incorporates a number of novel techniques to give users control over the release of their data. First, it introduces Operationfocused Access Control, a purposebased access control model that supports flexible and finegrain policies using typed operation labels. Second, our system allows RewardDriven Information Exchange. It provides a protocol for explicit communication of justifications and rewards and tunable privacy policies based on ongoing evaluation of the information exchange. Third, MUPPET includes a Purpose Detection Engine with an intuitive user interface for purpose management and supports explicit as well as implicit purpose activations based on context or authorizations. To validate our design, the MUPPET prototype has been integrated with a coupon personalization application for two different service providers in an experimental retail kiosk setting.
Maintaining Privacy In Electronic Transactions
, 1994
"... vi 1 Introduction 1 2 The Transaction Information Matrix 2 2.1 Parties Involved : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 2 2.2 Available Information : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 2 2.3 The Matrix : : : : : : : : : : : : : : : : : : : : : : : : ..."
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vi 1 Introduction 1 2 The Transaction Information Matrix 2 2.1 Parties Involved : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 2 2.2 Available Information : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 2 2.3 The Matrix
TECHNIQUES FOR SECURE ELECTRONIC TRANSACTIONS
"... As the use of Internet becomes a day to day activity of people, and purchases over the Internet is becoming an everyday necessity, secure methods of paying for such purchases have become very important. The need to provide the security of confidential information such as credit card numbers means th ..."
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that secure channels of communication are required. Cryptography plays a vital role in this. This paper looks at some of such cryptographic techniques used and some methods that are currently being used for monetary transactions.
Electronic Transactions on Numerical Analysis.
"... Abstract. We investigate the spectral behavior of preconditioned block Toeplitz matrices with small nonToeplitz blocks. These matrices have a quite different behavior than scalar or mulitlevel Toeplitz matrices. Based on the connection between Toeplitz and Hankel matrices we derive some negative re ..."
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Abstract. We investigate the spectral behavior of preconditioned block Toeplitz matrices with small nonToeplitz blocks. These matrices have a quite different behavior than scalar or mulitlevel Toeplitz matrices. Based on the connection between Toeplitz and Hankel matrices we derive some negative results on eigenvalue clustering for illconditioned block Toeplitz matrices. Furthermore, we identify Block Toeplitz matrices that are easy to solve by the preconditioned conjugate gradient method. We derive some useful inequalities that give information on the location of the spectrum of the preconditioned systems. The described analysis also gives information on preconditioning illconditioned Toeplitz Schur complement matrices and Toeplitz normal equations. Key words. Toeplitz, block Toeplitz, Schur complement, preconditioning, conjugate gradient method AMS subject classifications. 65F10, 65F15
Electronic Transactions on Numerical Analysis.
"... Abstract. We present, for some classes of ¢¤£¦ ¥ matrices,decompositions whose unit triangular ¢ factors ¥ and are simultaneously very well conditioned. Our examples include diagonally dominant matrices by rows and columns and their inverses, Stieljes matrices § andmatrices diagonally dominant by ..."
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Abstract. We present, for some classes of ¢¤£¦ ¥ matrices,decompositions whose unit triangular ¢ factors ¥ and are simultaneously very well conditioned. Our examples include diagonally dominant matrices by rows and columns and their inverses, Stieljes matrices § andmatrices diagonally dominant by rows or columns. We also show a construction of an accurate computation of ¢¨£¦ ¥ thedecomposition for § anymatrix diagonally dominant by rows or columns, which in turn can be applied to obtain an accurate singular value decomposition.
Electronic Transactions on Numerical Analysis.
"... Abstract. We develop and test a new mapping that can be applied to directed unweighted networks. Although not a “matrix function ” in the classical matrix theory sense, this mapping converts an unsymmetric matrix with entries of zero or one into a symmetric realvalued matrix of the same dimension t ..."
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Abstract. We develop and test a new mapping that can be applied to directed unweighted networks. Although not a “matrix function ” in the classical matrix theory sense, this mapping converts an unsymmetric matrix with entries of zero or one into a symmetric realvalued matrix of the same dimension that generally has both positive and negative entries. The mapping is designed to reveal approximate directed bipartite communities within a complex directed network; each such community is formed by two set of nodes S1 and S2 such that the connections involving these nodes are predominantly from a node in S1 and to a node in S2. The new mapping is motivated via the concept of alternating walks that successively respect and then violate the orientations of the links. Considering the combinatorics of these walks leads us to a matrix that can be neatly expressed via the singular value decomposition of the original adjacency matrix and hyperbolic functions. We argue that this new matrix mapping has advantages over other, exponentialbased measures. Its performance is illustrated on synthetic data, and we then show that it is able to reveal meaningful directed bipartite substructure in a network from neuroscience.
Electronic Transactions on Numerical Analysis.
"... Abstract. In this paper, we consider a class of hierarchically rank structured matrices that includes some of the hierarchical matrices occurring in the literature, such as hierarchically semiseparable (HSS) and certain H2matrices. We describe a fast (O(r3n log(n))) and stable algorithm to transfor ..."
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Abstract. In this paper, we consider a class of hierarchically rank structured matrices that includes some of the hierarchical matrices occurring in the literature, such as hierarchically semiseparable (HSS) and certain H2matrices. We describe a fast (O(r3n log(n))) and stable algorithm to transform this hierarchical representation into a socalled unitaryweight representation, as introduced in an earlier work of the authors. This reduction allows the use of fast and stable unitaryweight routines (or by the same means, fast and stable routines for sequentially semiseparable (SSS) and quasiseparable representations used by other authors in the literature), leading, e.g, to direct methods for linear system solution and for the computation of all the eigenvalues of the given hierarchically rank structured matrix. Key words. hierarchically semiseparable (HSS) matrix, H2matrix, low rank submatrix, tree, QR factorization, unitaryweight representation
Electronic Transactions on Numerical Analysis.
"... Abstract. A symplectic block reflector is introduced. The parallel with the Euclidean block reflector is studied. Some important features of symplectic block reflectors are given. Algorithms to compute a symplectic block reflector that introduces a desired block of zeros into a matrix are developed. ..."
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Abstract. A symplectic block reflector is introduced. The parallel with the Euclidean block reflector is studied. Some important features of symplectic block reflectors are given. Algorithms to compute a symplectic block reflector that introduces a desired block of zeros into a matrix are developed. Key words. Skewsymmetric scalar product, symplectic Householder transformation, block algorithm, symplectic QRfactorization AMS subject classifications. 65F30, 65F20, 15A57, 15A23
Electronic Transactions on Numerical Analysis.
"... Abstract. We consider the special case of the restarted Arnoldi method for approximating the product of a function of a Hermitian matrix with a vector which results when the restart length is set to one. When applied to the solution of a linear system of equations, this approach coincides with the m ..."
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Abstract. We consider the special case of the restarted Arnoldi method for approximating the product of a function of a Hermitian matrix with a vector which results when the restart length is set to one. When applied to the solution of a linear system of equations, this approach coincides with the method of steepest descent. We show that the method is equivalent to an interpolation process in which the node sequence has at most two points of accumulation. This knowledge is used to quantify the asymptotic convergence rate.
Electronic Transactions on Numerical Analysis.
"... Dedicated to Gene Golub on the occasion of his 75th birthday Abstract. A regression problem is separable if the model can be represented as a linear combination of functions which have a nonlinear parametric dependence. The GaussNewton algorithm is a method for minimizing the residual sum of squar ..."
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Dedicated to Gene Golub on the occasion of his 75th birthday Abstract. A regression problem is separable if the model can be represented as a linear combination of functions which have a nonlinear parametric dependence. The GaussNewton algorithm is a method for minimizing the residual sum of squares in such problems. It is known to be effective both when residuals are small, and when measurement errors are additive and the data set is large. The large data set result that the iteration asymptotes to a second order rate as the data set size becomes unbounded is sketched here. Variable projection is a technique introduced by Golub and Pereyra for reducing the separable estimation problem to one of minimizing a sum of squares in the nonlinear parameters only. The application of GaussNewton to minimize this sum of squares (the RGN algorithm) is known to be effective in small residual problems. The main result presented is that the RGN algorithm shares the good convergence rate behaviour of the GaussNewton algorithm on large data sets even though the errors are no longer additive. A modification of the RGN algorithm due to Kaufman, which aims to reduce its computational cost, is shown to produce iterates which are almost identical to those of the GaussNewton algorithm on the original problem. Aspects of the question of which algorithm is preferable are discussed briefly, and an example is used to illustrate the importance of the large data set behaviour.
Results 1  10
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