Towards a Statistical Framework for Source Anonymity in Sensor Networks

Rs- Contact for OFFER Price

Get Project

Project Summary

Price:- Contact for OFFER Price

AvailabilityYes

Year of Project2013

SRSJAVA

Project Detail

Towards a Statistical Framework for Source Anonymity in Sensor Networks IEEE Projects 2013 | Final year projects | BE Projects | Abstract: 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. Known as the source anonymity problem, this problem has emerged as an important topic in thesecurity of wireless sensor networks, with variety of techniques based on different adversarial assumptions being proposed. In this work, 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 of binary hypothesis testing with nuisance parameters. We then analyze existing solutions for designing anonymous sensor networks using the proposed model. We show how mapping source anonymity to binary 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 from analyzing real-valued sample points to binary codes, which opens the door for coding theory to be incorporated into the study of anonymous sensor networks. Finally, we discuss how existing solutions can be modified to improve their anonymity.

Towards a Statistical Framework for Source Anonymity in Sensor Networks. Sensor networks are deployed to sense, monitor, and report events of interest in a wide range of applications including, but are not limited to, military, health care, and animal tracking. In many applications, such monitoring networks consist of energy constrained nodes that are expected to operate over an extended period of time, making energy efficient monitoring an important feature for unattended networks. In such scenarios, nodes are designed to transmit information only when a relevant event is detected (i.e., event-triggered
transmission). Consequently, given the location of an event triggered node, the location of a real event reported by the node can be approximated within the node’s sensing range.

“SPEND LESS SCORE MORE”

Final Year Projects for all Computer Science Degrees, We provide Full Source Code, Complete Documentation and 24/7 Support for Online Configuration – Execution.

Most Affordable …..!!!!!
7 Years of Expertise …..!!!!!
More Than 1200 Projects …..!!!!!
More Than 4000 Facebook Fans …..!!!!!
24/7 Online Support for Execution …..!!!!!

As a part of project you will get below mentioned documentation along with SOURCE CODE,

1). BIBLIOGRAPHY
2). CONCLUSION
3). HARDWARE SOFTWARE SPECIFICATION
4). IMPLEMENTATION
5). INPUT DESIGN &OUTPUT DESIGN
6). INTRODUCTION
7). LITERATURE SURVEY
8). SCREENSHOT
9). SOFTWARE ENVIRONMENT
10). SYSTEM ANALYSIS
11). SYSTEM DESIGN
12). SYSTEM STUDY
13). SYSTEM TESTING

WE RUN PROJECT IN YOUR SYSTEM via TEAM VIEWER and SKYPE.

Need more details?
Email us : info@thebookmyproject.com OR ieee.project7@gmail.com
Call us : +91 98450 91623

Please refer your friends if they are looking for any projects.

Towards a Statistical Framework for Source Anonymity in Sensor Networks

Towards a Statistical Framework for Source Anonymity in Sensor Networks

Technology: JAVA and JAVA IEEE PROJECTS.Project Tags: Final Year Projects, IEEE 2013 Projects, and Mobile Computing.

Send To Friend

Get Project

Related Projects

Your Reviews