Location privacy protection against inference attacks
With the increasing usage of smart phones and tablets, privacy has become a concern for many people. While the GPS enabled handheld devices has been popular, the use of location-based systems has posed a privacy issue to the users. The use of location-based services, such as Google Maps, and social...
Saved in:
Main Author: | |
---|---|
Other Authors: | |
Format: | Final Year Project |
Language: | English |
Published: |
2015
|
Subjects: | |
Online Access: | http://hdl.handle.net/10356/65692 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
id |
sg-ntu-dr.10356-65692 |
---|---|
record_format |
dspace |
spelling |
sg-ntu-dr.10356-656922023-07-07T16:37:57Z Location privacy protection against inference attacks Chong Bao Yi Lu Rongxing School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering With the increasing usage of smart phones and tablets, privacy has become a concern for many people. While the GPS enabled handheld devices has been popular, the use of location-based systems has posed a privacy issue to the users. The use of location-based services, such as Google Maps, and social media for example, Facebook, Instagram which allow users to tag their current locations, have allowed attackers to track and collect information on the individuals. This project aims to understand the concept of Geo-indistinguishability, a novel and formal notion proposed in recent years to help to preserve the privacy of individuals using a location-based service, Google Maps. Further discussions on the concept of Geo-indistinguishability, and implementation of this concept into a physical form, such as an android application, to show how the concept works on a location-based service, will be discussed in this report. Bachelor of Engineering 2015-12-10T02:17:49Z 2015-12-10T02:17:49Z 2015 2015 Final Year Project (FYP) http://hdl.handle.net/10356/65692 en Nanyang Technological University application/pdf |
institution |
Nanyang Technological University |
building |
NTU Library |
continent |
Asia |
country |
Singapore Singapore |
content_provider |
NTU Library |
collection |
DR-NTU |
language |
English |
topic |
DRNTU::Engineering::Electrical and electronic engineering |
spellingShingle |
DRNTU::Engineering::Electrical and electronic engineering Chong Bao Yi Location privacy protection against inference attacks |
description |
With the increasing usage of smart phones and tablets, privacy has become a concern for many people. While the GPS enabled handheld devices has been popular, the use of location-based systems has posed a privacy issue to the users. The use of location-based services, such as Google Maps, and social media for example, Facebook, Instagram which allow users to tag their current locations, have allowed attackers to track and collect information on the individuals. This project aims to understand the concept of Geo-indistinguishability, a novel and formal notion proposed in recent years to help to preserve the privacy of individuals using a location-based service, Google Maps. Further discussions on the concept of Geo-indistinguishability, and implementation of this concept into a physical form, such as an android application, to show how the concept works on a location-based service, will be discussed in this report. |
author2 |
Lu Rongxing |
author_facet |
Lu Rongxing Chong Bao Yi |
format |
Final Year Project |
author |
Chong Bao Yi |
author_sort |
Chong Bao Yi |
title |
Location privacy protection against inference attacks |
title_short |
Location privacy protection against inference attacks |
title_full |
Location privacy protection against inference attacks |
title_fullStr |
Location privacy protection against inference attacks |
title_full_unstemmed |
Location privacy protection against inference attacks |
title_sort |
location privacy protection against inference attacks |
publishDate |
2015 |
url |
http://hdl.handle.net/10356/65692 |
_version_ |
1772828265380052992 |