DOCSLIB.ORG

Search Engine Privacy Protection in the System the Simple Solution: Trust

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text

Load more

Data Collection - Exploitation - Protection. 29 April 2011 S. S. Bhople (TUE) A.W. Huijgen(UT) S.L.C. Verberkt(UT) Outline • Data Being Collected • Local Privacy Protection • Privacy Protection in the System Outline • Data Being Collected • Microsoft • Google • Local Privacy Protection • Privacy Protection in the System Introduction Search Engines A program for the retrieval of data from a database or network, esp. the Internet. Examples •Google Search •Bing •AOL •… Question Will you tell your personal information to strangers on the street? NO Then why to do it online? Primer on information theory and privacy Identification of the person= facts about the person ? What facts can be considered to be important to identify the person? •Zip code •Date of birth •Gender •… Mathematics (Information Theory) Entropy Measure of the uncertainty associated with a random variable. Mathematical Formulation: The entropy H of a discrete random variable X with possible values {x1,.., xn} is H(X)=E(I(X)) E : expected value I : information content of X. If p denotes the probability mass function of X , then We Continue with this basic knowledge… Mathematical background Entropy (H): The quantity which allows us to measure how close a fact comes to revealing somebody's identity uniquely. How much entropy is needed to identify someone? Lets perform some simple calculations. Human population on Earth Approx. 7 billion? To identify someone from entire population 33 bits of information is needed. How? H=-Log (1/7000000000)= 33 bits (32.70 to be exact) Mathematics (continued..) Consider the case of Mr. X •Knowing his Birthday •ΔH= -log(1/365) = 8.51 •Knowing his zip-code (let 5641) and population in that area ΔH= -log(561/7 b) = 23.57 •Knowing the gender (here male) • ΔH = -log(1/2) = 1. Adding all above information total entropy reduces to 33.08. Therefore, Can we say that, we can uniquely identify Mr. X jus by knowing DOB, zip-code and gender? ΔH: reduction in entropy. Evidence Latanya Sweeney Points violating individual privacy •Retention of log of queries. •A log of queries associated with usernames. •A log queries more than a day, a month, an year. •Anonymized query data release. What is clear? Case study of AOL 2006 database scandal What was released? • Search data for roughly 658,000 anonymized users over a three month period from March to May. • There was no personally identifiable data provided by AOL with those records, but search queries themselves can sometimes include such information. • According to comScore Media Metrix, the AOL search network had 42.7 million unique visitors in May, so the total data set covered roughly 1.5% of May search users. Case study (continued) •20 million search records •U.S. searches Result •Violent debates. •Apology from AOL. Case study (continued) Some issues • Profiles of some AOL users were uniquely identified. Thelma Arnold, 62 years women. •Some scary stuff Check the profile 17556639.xls Case study (continued) Do you think this person wanted to do something bad? Can we use this to reduce crime rate? "I think freedom should be limited." -Barack Obama, 2006 Google Services offered •Search Google Search, Image Search, Video Search etc. •Advertising Adsense, Adwords, Double Click •Location Google Maps, Google Earth, Google Building Maker •Communication and Publishing Gmail, G-talk, Orkut, Google Public DNS •Online shopping Google Store, Google Checkout, Google Base Google Personal Productivity iGoogle, Google Toolbar, Google Desktop Business Solutions, Mobile, Development, Social Responsibility and Many More. Google collects data Google (Normal Search) •Search Engine Result •Additional Preferences Can Include Pages ◦Street Address •Country Code Domain ◦City •Query ◦State •IP address ◦Zip/Postal Code •Language •Clicks •Number of results •Safe search •Server Log ◦Query ◦URL ◦IP Address ◦Cookie ◦Browser ◦Date ◦Time Google collects data (continued) Google Personalized Search ◦ Personal Picture • Logs every website visited as a ◦ Usage result of a Google Search. ◦ Friends • Content analysis of visited ◦ Google Services Usage websites ◦ Amount of Logins Google Account Toolbar • Used as resource to compile • All Websites Visited information on individual users • Unique application number • Sign Up • Sends all visited 404s to Google ◦ Sign up date ◦ Username ◦ Password ◦ Alternate E-mail ◦ Location(Country) Google collects data (continued) •Toolbar Synchronization Function ◦ Stores Autofill info with Google Story is not very different for Account. other companies products. ◦ Sends structure of web forms to (more specifically other search Google. engines) • Safe Browsing ◦ Stores Response to Security Warnings • Stores Autofill Forms Data • Sends Spellcheck Data to Google Servers And the list continues… Search Engines : Big Boss? Do you get the feeling that someone is keeping a watch on you? Do you think your privacy is disturbed? A simple question Are IP addresses personal? “IP addresses recorded by every website on the planet without additional information should not be considered personal data, because these websites usually cannot identify the human beings behind these number strings.” Yes No ? Some facts • Websites like Google never store IP addresses devoid of context; instead, they store them connected to identity or behavior. • Google probably knows from its log files, for example, that an IP address was used to access a particular email or calendar account, edit a particular word processing document, or send particular search queries to its search engine. • By analyzing the connections woven throughout this mass of information, Google can draw some very accurate conclusions about the person linked to any particular IP address We are moving to a Google that knows more about you. -Google CEO Eric Schmidt, speaking to financial analysts February 9, 2005, as quoted in the New York Times the next day Why? • Google says it needs to store search queries and gather information on online activity to improve its search results and to provide advertisers with correct billing information that shows that genuine users are clicking on online ads. • Google promises to deliver its wonderful innovations by studying the behavior of individual. • To fight fraud and to improve data security. Anonymization by Google Technique followed by google to anonymize the IP Address • An IP address is composed of four equal pieces called octets. • Google stores the first three octets and deletes the last, claiming that this practice protects user privacy sufficiently. Really? "After nine months, we will change some of the bits in the IP address in the logs. After 18 months we remove the last eight bits in the IP address and change the cookie information...It is difficult to guarantee complete anonymization, but we believe these changes will make it very unlikely users could be identified.“ -Google Outline • Data Being Collected • Local Privacy Protection • Google Search • Beyond the Searching Page • Privacy Protection in the System Local Privacy Protection Google Search • Hide • Minimize • Obfuscate • Leave Hide Local Privacy Protection Google Search : Hide [1/2] Minimize Obfuscate Leave • Application Level . Scroogle.org . Startingpage.com . GoogleSharing Hide Local Privacy Protection Google Search : Hide [2/2] Minimize Obfuscate Leave • IP Level • HTTP Proxy • Socks Proxy • VPN • The Onion Routing project Hide Local privacy protection Minimize Google Search : Minimize [1/2] Obfuscate Leave • Startup Page • Sign Out • Autocomplete / Google Instant Hide Local privacy protection Minimize Google Search : Minimize [2/2] Obfuscate Leave • Clicktracking • User Script for Greasemonkey • OptimizeGoogle Add-on • Cookies • Javascript Hide Local privacy protection Minimize Google Search : Obfuscate Obfuscate Leave • TrackMeNot • User Scripts for Greasemonkey Hide Minimize Local privacy protection Obfuscate Google Search :: Leave Leave Local Privacy Protection Quick Summary • Hide • Minimize • Obfuscate • Leave Local Privacy Protection Beyond the Searching Page • Clicked Search Results • Browser Software Local Privacy Protection Clicked Search Results • Block Referers From Being Sent • SSL • HTTP POST Method • RefControl for Firefox • Block Google Analytics • Ghostery for Firefox • Block Google Ads • Adblock Plus for Firefox Local Privacy Protection Browser Software • General • Change Startup Page • Remove Google Toolbar • Mozilla Firefox • Disable Safebrowsing Feature and use WOT • Google Chrome • Use SRWare Iron Alternative • Windows Internet Explorer • Disable SmartScreen Filter Outline • Data Being Collected • Local Privacy Protection • Privacy Protection in the System • Trusting the Search Engine • Protection Against Information Leakage • Protection Against an Untrusted Search Engine Privacy protection in the system The Simple Solution: Trust • Establishing Trust • Trust the Search Engine to Respect your Privacy • End User Agreements • Law Privacy protection in the system Information Leakage • Using an untrusted channel • Sending search terms or retrieving results • Retrieving personalized search term suggestions • Retrieving search history • With a hijacked session • Retrieving search history • Retrieving search history using personalized search term suggestions Privacy protection in the system Information Leakage • Example of misuse of personalized search suggestions: • Malicious user supplies common two-letters prefixes: pr • Suggest will reply with suggestions: privacy protection protocols • If there are 3 suggestions, the malicious
Recommended publications
  • Understanding the Value of Arts & Culture | the AHRC Cultural Value

    Understanding the Value of Arts & Culture | the AHRC Cultural Value

    Understanding the value of arts & culture The AHRC Cultural Value Project Geoffrey Crossick & Patrycja Kaszynska 2 Understanding the value of arts & culture The AHRC Cultural Value Project Geoffrey Crossick & Patrycja Kaszynska THE AHRC CULTURAL VALUE PROJECT CONTENTS Foreword 3 4. The engaged citizen: civic agency 58 & civic engagement Executive summary 6 Preconditions for political engagement 59 Civic space and civic engagement: three case studies 61 Part 1 Introduction Creative challenge: cultural industries, digging 63 and climate change 1. Rethinking the terms of the cultural 12 Culture, conflict and post-conflict: 66 value debate a double-edged sword? The Cultural Value Project 12 Culture and art: a brief intellectual history 14 5. Communities, Regeneration and Space 71 Cultural policy and the many lives of cultural value 16 Place, identity and public art 71 Beyond dichotomies: the view from 19 Urban regeneration 74 Cultural Value Project awards Creative places, creative quarters 77 Prioritising experience and methodological diversity 21 Community arts 81 Coda: arts, culture and rural communities 83 2. Cross-cutting themes 25 Modes of cultural engagement 25 6. Economy: impact, innovation and ecology 86 Arts and culture in an unequal society 29 The economic benefits of what? 87 Digital transformations 34 Ways of counting 89 Wellbeing and capabilities 37 Agglomeration and attractiveness 91 The innovation economy 92 Part 2 Components of Cultural Value Ecologies of culture 95 3. The reflective individual 42 7. Health, ageing and wellbeing 100 Cultural engagement and the self 43 Therapeutic, clinical and environmental 101 Case study: arts, culture and the criminal 47 interventions justice system Community-based arts and health 104 Cultural engagement and the other 49 Longer-term health benefits and subjective 106 Case study: professional and informal carers 51 wellbeing Culture and international influence 54 Ageing and dementia 108 Two cultures? 110 8.
  • Cloak and Swagger: Understanding Data Sensitivity Through the Lens of User Anonymity

    Cloak and Swagger: Understanding Data Sensitivity Through the Lens of User Anonymity

    Cloak and Swagger: Understanding Data Sensitivity Through the Lens of User Anonymity Sai Teja Peddinti∗, Aleksandra Korolova†, Elie Bursztein†, and Geetanjali Sampemane† ∗Polytechnic School of Engineering, New York University, Brooklyn, NY 11201 Email: [email protected] †Google, 1600 Amphitheatre Parkway, Mountain View, CA 94043 Email: korolova, elieb, [email protected] Abstract—Most of what we understand about data sensitivity In this work we explore whether it is possible to perform is through user self-report (e.g., surveys); this paper is the first to a large-scale behavioral data analysis, rather than to rely on use behavioral data to determine content sensitivity, via the clues surveys and self-report, in order to understand what topics that users give as to what information they consider private or sensitive through their use of privacy enhancing product features. users consider sensitive. Our goal is to help online service We perform a large-scale analysis of user anonymity choices providers design policies and develop product features that during their activity on Quora, a popular question-and-answer promote user engagement and safer sharing and increase users’ site. We identify categories of questions for which users are more trust in online services’ privacy practices. likely to exercise anonymity and explore several machine learning Concretely, we perform analysis and data mining of the approaches towards predicting whether a particular answer will be written anonymously. Our findings validate the viability of usage of privacy features on one of the largest question-and- the proposed approach towards an automatic assessment of data answer sites, Quora [7], in order to identify topics potentially sensitivity, show that data sensitivity is a nuanced measure that considered sensitive by its users.
  • Cloud Computing and Related Laws

    Cloud Computing and Related Laws

    Cloud Computing and Related Laws Law Offices of Salar Atrizadeh Online Privacy In general, privacy falls under two categories: 1. Corporate privacy 2. Personal privacy Corporate Privacy . It concerns the protection of corporate data from retrieval or interception by unauthorized parties . Security is important for protection of trade secrets, proprietary information, and privileged communications . The failure to maintain confidentiality can result in a loss of “trade secret” status . See Civil Code §§ 3426 et seq. Corporate Privacy . The recent trends in outsourcing have increased the risks associated with “economic espionage” . In fact, manufacturers should be cautious when transferring proprietary technology to overseas partners because foreign governments sponsor theft . See 18 U.S.C. §§ 1831 et seq. (e.g., economic espionage, theft of trade secrets) Helpful Policies . Identify and label confidential information . Restrict access to confidential information . Use encryption – e.g., truecrypt.org, axantum.com . Use firewall and secure username/password . Use software that detects trade secret theft – e.g., safe-corp.biz . Include warnings in privileged correspondence (e.g., “this email contains privileged communications”) Helpful Policies . Provide computers without hard drives + Prohibit use of removable storage (e.g., flash drives) . Audit employee computers . Prohibit and/or monitor external web-based email services . Execute Confidentiality and Non-disclosure Agreements . Execute Computer-Use Policies Personal Privacy . Constitution . Federal: Fourth Amendment protects against unreasonable searches and seizures . State: California Constitution, under Art. I, § 1 recognizes right to individual privacy . Federal computer crimes . Electronic Communications Privacy Act – 18 U.S.C. §§ 2510 et seq. Privacy Act – 5 U.S.C. § 552a . Computer Fraud and Abuse Act – 18 U.S.C.
  • Strategic Management Can New Players Still Compete with the Giants?

    Strategic Management Can New Players Still Compete with the Giants?

    Master Thesis Business Administration – Strategic Management Can new players still compete with the giants? Analyzing the creation of new platforms and how their strategies change overtime in the music platform industry Author: Maikel Coeleman Student number: S4357736 Supervisor: Dr. S. Khanagha Second examiner: Dr. G.W. Ziggers Date: 25-8-2018 1 Table of contents 1. Introduction ......................................................................................................................................... 4 1.1 Problem Statement ....................................................................................................................... 5 1.2 Relevance ...................................................................................................................................... 8 1.3 Outline Thesis ................................................................................................................................ 9 2. Theoretical background ..................................................................................................................... 10 2.1 How to deal with the dilemmas of platform creation ................................................................. 10 2.2 Roger’s diffusion of innovations .................................................................................................. 10 2.3 First-, second- & late-movers ...................................................................................................... 17 3. Methodology ....................................................................................................................................
  • Statement on Internet Search Engines by the Spanish Data

    Statement on Internet Search Engines by the Spanish Data

    Statement on Internet Search Engines Spanish Data Protection Agency 1st December 2007 1. The importance of search engines in information society Technology developments have opened up new possibilities of creating and accessing information on the Internet, and this situation requires that we consider the repercussions of technology on the rights of individuals—in principle, such repercussions are neutral. The Spanish Data Protection Agency (AEPD) has taken the initiative of analysing the privacy policies of the largest global companies providing search engine services on the Internet. To this end it collected information from Google, Microsoft and Yahoo!, said information being completed via meetings with the global privacy controllers of these corporations in Europe and the United States. We must underscore the huge importance, owing to the volume of data that is processed and the characteristics of that processing, of search engine services on the Internet (hereinafter, search engines), the main function of which is to provide lists of results relating to a search, such as addresses and files stored on web serves, by entering key words, thus arranging all of the information available on the Internet and making it more accessible. In addition, search engines usually provide customised services, allowing people to register by giving an email address and a password.1 In Spain, the fact that these are sensitive issues was shown by the recent appearance of the Director of the AEPD before the Constitutional Commission of the Congress on 28th
  • Privacy Seminar 2

    Privacy Seminar 2

    14-2-2014 Dan Perjovschi Privacy Seminar 2. Privacy: an overview Jaap-Henk Hoepman Digital Security (DS) Radboud University Nijmegen, the Netherlands @xotoxot // [email protected] // www.cs.ru.nl/~jhh Dan Perjovschi, 2007 Jaap-Henk Hoepman // Radboud University Nijmegen // 14-2-2014 // Privacy: an overview 2 Privacy Dimensions the right to be let alone relational privacy informational privacy / what is privacy self determination according to you? corporeal privacy locational/spatial privacy privacy spheres Jaap-Henk Hoepman // Radboud University Nijmegen // 14-2-2014 // Privacy: an overview 3 Jaap-Henk Hoepman // Radboud University Nijmegen // 14-2-2014 // Privacy: an overview 4 Don’t confuse these concepts! 7 types of privacy privacy of ● the person, security privacy ● behaviour and action, ● personal communication, ● data and image, ● thoughts and feelings, ● location and space, and data protection ● association (including group privacy). Finn, R.L., Wright, D., and Friedewald, M.: Seven types of privacy. CPDP 2012 Clarke, R.: Introduction to Dataveillance and Information Privacy, and Definitions of Terms, 1997 Jaap-Henk Hoepman // Radboud University Nijmegen // 14-2-2014 // Privacy: an overview 5 Jaap-Henk Hoepman // Radboud University Nijmegen // 14-2-2014 // Privacy: an overview 6 1 14-2-2014 Different definitons Contextual integrity The right to be let alone ● [Warren & Brandeis, 1890] Informational self-determination: The right to determine for yourself when, how and to what extend information about you is communicated to others
  • Internet Based Distribution and Visualization of a 3D Model of the University of Cologne Campus

    Internet Based Distribution and Visualization of a 3D Model of the University of Cologne Campus

    3rd ISDE DIGITAL EARTH SUMMIT 12-14 June, 2010, Nessebar, Bulgaria INTERNET BASED DISTRIBUTION AND VISUALIZATION OF A 3D MODEL OF THE UNIVERSITY OF COLOGNE CAMPUS Willmes, C.*, Baaser, U., Volland, K. and G. Bareth Institute of Geography (GIS & RS), University of Cologne Albertus-Magnus-Platz, 50923 Cologne, Germany *corresponding author; Phone: +49-(0)221-470-6234, [email protected] Abstract Visualization of 3D geodata integrated into a web browser based user interface is still a key issue in geoinformation science research. In a short overview of state of the art solutions for this demand, the key advantages and disadvantages of each of those solutions are lined out. As a solution which combines most of the advantages identified before, a CityGML based 3D model of the University of Cologne Campus and the setup of an OGC conform Web Perspective View Service for internet based visualization of this model is described. Keywords 3D geodata visualization, 3D model, 3D buildings, CityGML, 3D-SDI, WPVS. 0. INTRODUCTION In this paper an implementation of a CityGML (Kolbe et. al 2008) based 3D model of the University of Cologne Campus buildings and the setup of an OGC Web Perspective View Service (WPVS) based visualization of this model is presented. The considerations to choose the WPVS technique for the system setup and the implementation of this web service will be described in the following of this paper. Study area for this project is the University of Cologne Campus area for which a GIS is available, the CampusGIS (CampusGIS 2010). The CampusGIS provides general and spatial campus information, e.
  • Insideradio.Com

    Insideradio.Com

    800.275.2840 MORE NEWS» insideradio.com THE MOST TRUSTED NEWS IN RADIO WEDNESDAY, JANUARY 7, 2015 Radio 2015: Big ideas on the Washington agenda. It will be the year of copyrights, predicts one radio industry lobbyist, as a new Republican-controlled Congress takes over and big issues dominate the agenda. Inside-the-Beltway players say the issue for 2015 will be how far lawmakers can get with their lofty goals, a list that includes many potential pitfalls for radio. While radio royalties may win the prize for best staying power across multiple sessions, radio’s biggest challenge in the 114th Congress may have nothing to do with music. “The fallout from the election strongly suggests that tax reform is one of the first things that are going to be on the table,” says Dan Jaffe, head of the Association of National Advertisers’ government relations office in Washington. It’s one of the few areas where there seems to be agreement between the White House and Capitol Hill, with an interest in, at the very Radio 2015: All this least, stretching out the timeline for marketers looking to deduct their advertising expense. Tax reform week Inside Radio will examine the also polls well with voters. “It’s the biggest threat to the ad deduction ever,” Jaffe warns. A coalition biggest issues facing of groups is working the backrooms of Congress, trying to maintain the status quo. But with an issue broadcasters, along that crosses partisan lines, no one is ready to predict which way a tax reform bill could come together.
  • Thesis.Pdf (2.311Mb)

    Thesis.Pdf (2.311Mb)

    Faculty of Humanities, Social Sciences and Education c Google or privacy, the inevitable trade-off Haydar Jasem Mohammad Master’s thesis in Media and documentation science … September 2019 Table of Contents 1 Introduction ........................................................................................................................ 1 1.1 The problem ............................................................................................................... 1 1.2 Research questions ..................................................................................................... 1 1.3 Keywords ................................................................................................................... 2 2 Theoretical background ...................................................................................................... 3 2.1 Google in brief ........................................................................................................... 3 2.2 Google through the lens of exploitation theory .......................................................... 4 2.2.1 Exploitation ................................................................................................ 4 2.2.2 The commodification Google’s prosumers ................................................ 5 2.2.3 Google’s surveillance economy ................................................................. 7 2.2.4 Behaviour prediction .................................................................................. 8 2.2.5 Google’s ‘playbor’
  • Introduction How Do You Turn Your Passion for App Development Into a Serious Business? the App Developer Business Kit by Admob Is Here to Help

    Introduction How Do You Turn Your Passion for App Development Into a Serious Business? the App Developer Business Kit by Admob Is Here to Help

    Introduction How do you turn your passion for app development into a serious business? The App Developer Business Kit by AdMob is here to help. You’ve got a brilliant idea for an app that strikes when you least expect it! Fast forward two months and your app is built, it works and all your friends have tested it (but you’ve told only a handful of work colleagues about it). You release it but you’re not quite sure what to do next. The Business Kit is a guide for entrepreneurial developers to turn their app into a successful business. It has four sections packed with tips and advice from developers and industry leaders. From an idea to an app Understand the principles for success, and hear advice from some of the world’s top app developers. Growth Attract more users, expand into more markets and use analytics to improve your app. Think big How to go from one great app to a portfolio of great apps and important considerations for expanding your business. Nine takeaways Nine tips to help you become a more successful developer. Why apps, why now? Annual global revenue for apps reached $27BN in 2013[1], and is forecast to climb to $75BN by 2017[2], with sophisticated developers opting for freemium revenue models rather than paid. What’s driving this enor- mous growth? Three important trends: The appetite for smartphones is immense. Sales of smartphones surpassed sales of feature phones tration exceeds 50%.[4] People are spending more time on mobile devices. Mobile is becoming the most popular way to get online, exceeding time spent using desktop computers.[5] Users love apps.
  • Towards Automatic 3D Reconstruction of Pitched Roofs in Monocular Satellite/Aerial Images

    Towards Automatic 3D Reconstruction of Pitched Roofs in Monocular Satellite/Aerial Images

    TOWARDS AUTOMATIC 3D RECONSTRUCTION OF PITCHED ROOFS IN MONOCULAR SATELLITE/AERIAL IMAGES by Zachary Blair B.A.Sc., Simon Fraser University, 2008 a Thesis submitted in partial fulfillment of the requirements for the degree of Master of Applied Science in the School of Engineering Science Faculty of Applied Sciences c Zachary Blair 2012 SIMON FRASER UNIVERSITY Fall 2012 All rights reserved. However, in accordance with the Copyright Act of Canada, this work may be reproduced without authorization under the conditions for \Fair Dealing." Therefore, limited reproduction of this work for the purposes of private study, research, criticism, review and news reporting is likely to be in accordance with the law, particularly if cited appropriately. APPROVAL Name: Zachary Blair Degree: Master of Applied Science Title of Thesis: Towards Automatic 3D Reconstruction of Pitched Roofs in Monocular Satellite/Aerial Images Examining Committee: Dr. Ljiljana Trajkovic Chair Dr. Parvaneh Saeedi, Senior Supervisor Dr. Shahram Payandeh, Supervisor Dr. Ivan Bajic, Internal Examiner Date Approved: October 22, 2012 ii Partial Copyright Licence Abstract This thesis presents a novel method for estimating the three-dimensional shape of pitched roofs in monocular satellite/aerial images by utilizing the acquisition geometry (both sun and camera). This method consists of four steps: rooftop extraction, texture and vent removal, identification of planar sections, and 3D roof model generation. During the fourth step, 3D reconstruction candidates are partially rendered and iteratively compared against the original image to evaluate a fitness function. The experimental results illustrate that the proposed framework can derive 3D building rooftop models, including estimates for roof pitch, from single satellite/aerial images in situations where previous techniques fail.
  • Utilização De Ferramentas E Serviços Google Para O Desenvolvimento De Projetos De Engenharia, Arquitetura E Urbanismo

    Utilização De Ferramentas E Serviços Google Para O Desenvolvimento De Projetos De Engenharia, Arquitetura E Urbanismo

    UTILIZAÇÃO DE FERRAMENTAS E SERVIÇOS GOOGLE PARA O DESENVOLVIMENTO DE PROJETOS DE ENGENHARIA, ARQUITETURA E URBANISMO 1. Introdução A empresa Google Inc. nasceu em 1998, quando Larry Page e Sergey Brin, dois estudantes da Stanford University, resolveram criar um sistema de busca de hipertextos na internet. A palavra “Google” é uma brincadeira com a palavra “googol”, o termo matemático para 1 seguido de 100 zeros, que se encaixa muito bem no objetivo de construir um sistema de busca de larga escala (BRIN; PAGE, 1998). O Google desenvolveu e disponibiliza, muitas vezes de forma gratuita, diversas ferramentas e serviços, tais como: Google Web Search, Google Translator, Google Mail (Gmail), Google Maps, Google StreetView, Google Earth, Google SketchUp, Google Building Maker, Google Image Search, Google Play, Google Drive, Google Chrome, YouTube, Orkut, Picasa, entre outros. A lista completa pode ser encontrada em Google Inc. (2013a). Segundo a empresa, a missão do Google é organizar a informação mundial e fazê-la universalmente acessível e útil (GOOGLE INC., 2013b). Muitas destas ferramentas oferecidas pelo Google podem ser utilizadas para o desenvolvimento de projetos preliminares e estudo de viabilidade em áreas como Engenharia, Arquitetura e Urbanismo. O geoprocessamento no Google começou em 2004, quando o mesmo adquiriu a empresa de mapeamento digital Keyhole e lançou o Google Maps e o Google Earth em 2005. Com o passar do tempo, o Google Maps evoluiu muito e hoje permite a visualização de trânsito em tempo real, a geração de rotas a partir de pontos de origem e destino e a visualização imagens ao nível da rua (StreetView).