Evaluating Musculoskeletal Complications Among Individuals With Diabetes Mellitus

Dr. Simran Maheshwari; Dr. Subhan Quraishi; Dr. Babita Ghodke

Volume : II, Issue : XI, November - 2013

Evaluating Musculoskeletal Complications Among Individuals With Diabetes Mellitus

Dr. Simran Maheshwari, Dr. Subhan Quraishi, Dr. Babita Ghodke

Abstract :

In certain applications, the locations of events reported by a sensor network need to remain anonymous. That is, unauthorized observers must be unable to detect the origin of such events by analyzing the network traffic. We analyze two kinds of problems: Communication overhead and computational load problem. In this paper, we present a new framework for modeling, analyzing, and evaluating anonymity in sensor networks. The novelty of the proposed framework is twofold: first, it introduces the notion of �interval indistinguishability� and provides a quantitative measure to model anonymity in wireless sensor networks; second, it maps source anonymity to the statistical problem We showed that the current approaches for designing statistically anonymous systems introduce correlation in real intervals while fake are uncorrelated. We show how mapping source anonymity to statistical hypothesis testing with nuisance Parameters leads to converting the problem of exposing private source information into searching for an appropriate data transformation that removes or minimize the effect of the nuisance information. By doing so, we transform the problem of analyzing real valued sample points to binary codes, which opens the door for coding theory to be incorporated into the study of anonymous networks. In existing work, unable to detect unauthorized observer in network traffic. But our work mainly based on enhances their source anonymity against correlation test. The main goal of source location privacy is to hide the existence of real events.