Quantifying Privacy: A Novel Entropy-Based Measure of Disclosure Risk

It is well recognised that data mining and statistical analysis pose a serious treat to privacy. This is true for financial, medical, criminal and marketing research. Numerous techniques have been proposed to protect privacy, including restriction and data modification. Recently proposed privacy models such as differential privacy and k-anonymity received a lot of attention and for the latter there are now several improvements of the original scheme, each removing some security shortcomings of the previous one. However, the challenge lies in evaluating and comparing privacy provided by various techniques. In this paper we propose a novel entropy based security measure that can be applied to any generalisation, restriction or data modification technique. We use our measure to empirically evaluate and compare a few popular methods, namely query restriction, sampling and noise addition.Comment: 20 pages, 4 figure

On the Security of Noise Addition for Privacy in Statistical Databases

Noise addition is a family of methods used in the protection of the privacy of individual data (microdata) in statistical databases

Hyperelastic Model of Anisotropic Fiber Reinforcements within Intestinal Walls for Applications in Medical Robotics

The development of an anatomically realistic model of intestinal tissue is essential for the progress of several clinical applications of medical robotics. A hyperelastic theory of the layered structure of the intestine is proposed in this paper to reproduce its purely elastic passive response from the structural organization of its main constituents. The hyperelastic strain energy function is decoupled into an isotropic term, describing the ground biological matrix, and an anisotropic term, describing the single contributions of the directional fiber-reinforcements. The response of the muscular coat layer has been modeled as a stiffening effect due to two longitudinal and circular muscular reinforcements. The contribution of the submucosa has been described from a uniform distribution of fibrillar collagen in a cross-ply arrangement. An experimental procedure has been proposed in order to characterize the passive response of porcine intestinal samples from planar uniaxial traction and shear tests. The experimental data have been non-linearly fitted in the least square sense with the results of the theoretical predictions. The mechanical parameters have been fitted with high accuracy (R-min(2) = 0.9329, RMSEmax = 0.01167), demonstrating the ability of the model to reproduce the mechanical coupling due to the presence of multiple directional reinforcements. The fundamental mechanical role of collagen morphology in the passive biomechanical behavior of intestinal wall is demonstrated. These results may drive a better understanding of the key factors in growth and remodeling of healthy and diseased tissue, together with numerous applications in robotic endoscopy, minimally invasive surgery, and biomedical research.TNECN

Virtual reality and spatial ability

Published in: IEEE Proceedings. VR 2005. Virtual Reality, 2005The article of record as published may be found at http://dx.doi.org/10.1109/VR.2005.1492805VR technology provides unique assets for assessing, training and rehabilitating spatial abilities. Its capacity for creating, presenting, and manipulating dynamic three-dimensional (3D) objects and environments in a consistent manner enables the precise measurement of human interactive performance with these stimuli. VE spatial ability testing and training systems may provide ways to target cognitive processes beyond what exists with methods relying on 2D pencil and paper representations of 3D objects (or methods using actual real objects) that are typically found with traditional tools in this area. Traditional methods are often limited by poor depth, motion, and 3D cues needed for proper stimulus delivery. In addition they have limited capacity for the precise measurement of responses. VR offers the potential to address these variables in an ecologically valid manner (functional simulations) without the loss of experimental control common with naturalistic studies in this area relying on observational methods

Preventing Interval-based Inference by Random Data Perturbation

Random data perturbation (RDP) method is often used in statistical databases to prevent inference of sensitive information about individuals from legitimate sum queries. In this paper, we study the RDP method for preventing an important type of inference: interval-based inference

Not Available

Not AvailableThe Potyviridae family is one of the largest and economically most significant families of plant viruses, owing to their effects on crops globally. Sugarcane streak mosaic virus (SCSMV), a member of the genus Poacevirus, of this family, an important viral pathogen affects the sugarcane production in India. The genome has a single open reading frame that is translated in to a large polypeptide and consequently cleaved into functional proteins. This virus causes mosaic of sugarcane along with the Sugarcane mosaic virus (SCMV) which is a serious disease causing varietal degeneration reported from India in 1999 and later has been reported from geographically different Asian countries. The coding region for P1 peptidase is located at the very beginning of the viral genome of the family Potyviridae. P1 was thought of as serine peptidase with RNA-binding activity and with possible influence in cell-to-cell viral spreading. In order to unveil its mechanism of evolution we initiated the study by characterizing 10 P1 gene of Indian isolates and the sequences were compared with previously reported SCSMV isolates from different countries. Comparison of all of the sequenced virus isolates revealed a high level of diversity in the P1 gene (83–98% nt sequence identity; 87–100% aa sequence identity), and the Indian isolates were found to be the most divergent (up to 9% variation at the amino acid level). Phylogenetic analysis revealed clustering of 17 SCSMV isolates into two groups. Group I included isolates from India (except SCSMV-TPT) and Pakistan, and group II consisted of isolates from Japan, Indonesia, Thailand and SCSMV-TPT. The results obtained from phylogenetic study were further supported with the SNPs (single nucleotide polymorphism), INDELs (insertion and deletion) and evolutionary distance analysis. A significant proportion of recombination sites were found at the N terminal region of P1 gene of Indian isolates. Analysis of selection pressure indicated that the P1 gene of Indian SCSMV isolates is under strong negative selection. It is likely that recombination, along with strong negative selection, enhances the speed of elimination of lethal mutations in the P1 gene of Indian SCSMV isolates.Not Availabl