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Network Architectures and Services, Georg Carle Faculty of Informatics Technische Universitt Mnchen, Germany Bachelor Thesis Visual analysis of anonymized location and movement data Supervisor: Prof. Dr.-Ing. Georg Carle Advisor:

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Network Architectures and Services, Georg Carle Faculty of Informatics Technische Universität München, Germany

Bachelor Thesis

Visual analysis of anonymized location and movement data

Supervisor: Prof. Dr.-Ing. Georg Carle Advisor: Dipl.-Inf. Johann Schlamp Timo Lamprecht 6th Semester SS13 Bachelor Computer Science

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Agenda

➢ Goals & Benefits ➢ Basics

MEASRDROID, related work, 2-d-tree, k-anonymity

➢ Design ➢ Implementation ➢ Evaluation

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Goals & Benefits

Goals:

➢ Visualization

(Street map, dynamcis e.g. zoom-function, time bar)

➢ Further use

(Adaptable or expandable, generic objects)

➢ Data management

(Increasing amount of data, acceptable performance)

➢ Anonymization

(Sensitive location data)

Benefits:

➢ Study behaviour of people

(soccer matches, demonstrations, concerts)

➢ Traffic infrastructure

(analysing frequently used routes)

➢ Public transportation

(analysing different time intervals)

➢ Traffic planning

(adjust traffic lights)

➢ Personal navigation

(avoid rush-hour traffic)

Display of places of locations and movement tendencies

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Basics - MEASRDROID

Measured and send every 15 minutes (by default)

Database Server Android devices

with MEASRDOID application installed

Sensor information

Gravity
Gyroscope
Humidity
Light
Magnetic field

Network information

Reachable WLAN hotspots
Telephony information
IPv4 and IPv6 routes

Location information

Position
Satellite information

General information

Kernel build
Timestamp
Client ID

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Basics - Related work

Community Seismic Network

➢ Display of all participating

seismic devices

➢ Visualization with rectangles ➢ Intuitive ➢ Limited number of objects ➢ Anonymization maintained?

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Basics - k-anonymity

Motivation:

Non-anonymized data can cause massive legal problems → take anonymity seriously

➢ Consists of Identifiers, Quasi-Identifiers,

Sensitive Data

➢ Each combination of Quasi-Identifiers must

be merged to at least k times the same value

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Basics - 2-d-tree

➢ Each node splits a plane into 2 half-planes ➢ Splitting-coordinate alternates ➢ Each leaf is a 2-dimensional point ➢ Has not to be balanced ➢ Well searchable data structure: O(log(n))

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Design

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Design – Data security

No sensitive data outside the database server → Prevent data leak even if web server gets compromised No access rights to database server → Database server initiates data transfer

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Design – Data protection

Problem:

➢ Handling of sensitive location data ➢ Avoid showing precise positions of single users

(Problem: Telephone book + Single house) Solution:

➢ Show areas instead of single positions ➢ Aggregate with help k-anonymity ➢ There have to be at least k clients in an area

Interpretation of k-anonymity

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Design - Visualization

➢ Location analysis

Rectangles to mark areas Available if there are at least k persons in the area Opacity should depend on available information for the area

➢ Movement analysis

Arrows to mark directions Available if at least k persons went in the same direction Minimal length of movement (dependent on zoom level) necessary for counting Stroke weight depends on the number of clients moved

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Design - 2-d-tree adaption

➢ First split at 0° west ➢ Equal sized half-planes ➢ Increasingly precise grid evolves ➢ Relation between tree level and zoom-level of street map

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Implementation

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Implementation - Form

➢ Data packages available on web server ➢ Dynamic data requests to minimize network traffic ➢ Data package depends on selected time settings

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Implementation - 2-d-tree buildup

➢ Information aggregation in each node ➢ Calculation of all necessary information for the drawable object ➢ Recursive method ➢ Check on anonymization while build up

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Implementation – File transfer

Web server Database server Client

Creation of data file

Sending requested data file Dynamic data request via JS AJAX Frequent synchronization of completely processed data files 16 09/10/2013 Timo Lamprecht – Visual analysis of anonymized location and movement data

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Evaluation

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Evaluation – GPS data

➢ Overall distance travelled: 65,000 kilometres ➢ 15,000 GPS measurements available ➢ Number of satellites used per measurement:

➢ American NAVSTAR GPS consists of only 32 satellites but ~60 different

and unique GPS signals measured → Ground based augmentation system used (e.g. Munich airport)

Usually 4 satellites necessary (4 dimensions of room and time)
Average between 5 and 6 satellites
Probably measurement errors with just 2 satellites used
Measurement of 3 from 4 dimensions possible with 3 satellites
Precise position with a lot of satellites

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Evaluation – Location analysis

Global overview Overview over distribution

f MEASRDROID

application Mostly all measurements were done in Europe High measurement density around Munich Almost no measurements in north east of Germany Run of Autobahn visible

(Munich → Nuremberg → Kassel, Munich → Augsburg → Stuttgart)

Precise rectangles between Munich and Garching High density along this axis

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Evaluation – Movement analysis

➢ A lot of movement between Munich

and Garching

➢ Bigger arrows in north-south direction

than in east-west direction → more people moved in north-south direction

➢ Almost no movement out of the axis

Munich – Garching - Neufahrn

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Network Architectures and Services, Georg Carle Faculty of Informatics Technische Universität München, Germany

Thank you

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Backup

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Basics - GPS

➢ Position determination with satellites ➢ NAVSTAR-II as most used system ➢ 2010: GLONASS, 2020: GALILEO, Beidou ➢ At least 24 active satellites necessary for global coverage ➢ Precision up to 10 meters

Functionality:

➢ Broadcast of position and time ➢ Measurement of time difference to determine radius ➢ Lack of high precision clocks in GPS receivers ➢ 4th satellite to measure 4th dimension (time)

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Design - Achievements

Achievements:

➢ Overall number of GPS measurements ➢ Overall distance travelled ➢ Number of GPS measurements within 1° x 1° ➢ Number of GPS measurements within 100 seconds

Achievement server Database server

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Overview

SQL alchemy, Python

Make data anonymous Build up of data structure Integrate data into a street map Presentation

n a website

JavaScript, HTML, CSS JSON, existing server scripts

Database server Web server Client Transfer

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Implementation – Generic objects

➢ JavaScript prototype framework to simulate classes

➢ Set of functions

Constructor: function * *.prototype.createGoogleObject = function *.prototype.setVisible = function *.prototype.getInformationString = function *.prototype.recalculateAttributes = function ( * = class name )

➢ Necessary for each supported object type

(rectangle, circle, arrow, …) to ensure expandability

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Implementation – SQL alchemy

➢ SQL alchemy ➢ Object oriented writing ➢ Selection of all necessary information ➢ Filter on time interval

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Implementation – Storing of 2-d-tree

➢ Recursive method ➢ Latitude, longitude, children: Node information and tree structure ➢ Attributes: Information for drawable object ➢ Information: Additional information (number of persons, size of area)

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