EPIC Do Not Track Statement 120910
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The Web Never Forgets: Persistent Tracking Mechanisms in the Wild
The Web Never Forgets: Persistent Tracking Mechanisms in the Wild Gunes Acar1, Christian Eubank2, Steven Englehardt2, Marc Juarez1 Arvind Narayanan2, Claudia Diaz1 1KU Leuven, ESAT/COSIC and iMinds, Leuven, Belgium {name.surname}@esat.kuleuven.be 2Princeton University {cge,ste,arvindn}@cs.princeton.edu ABSTRACT 1. INTRODUCTION We present the first large-scale studies of three advanced web tracking mechanisms — canvas fingerprinting, evercookies A 1999 New York Times article called cookies compre and use of “cookie syncing” in conjunction with evercookies. hensive privacy invaders and described them as “surveillance Canvas fingerprinting, a recently developed form of browser files that many marketers implant in the personal computers fingerprinting, has not previously been reported in the wild; of people.” Ten years later, the stealth and sophistication of our results show that over 5% of the top 100,000 websites tracking techniques had advanced to the point that Edward employ it. We then present the first automated study of Felten wrote “If You’re Going to Track Me, Please Use Cook evercookies and respawning and the discovery of a new ev ies” [18]. Indeed, online tracking has often been described ercookie vector, IndexedDB. Turning to cookie syncing, we as an “arms race” [47], and in this work we study the latest present novel techniques for detection and analysing ID flows advances in that race. and we quantify the amplification of privacy-intrusive track The tracking mechanisms we study are advanced in that ing practices due to cookie syncing. they are hard to control, hard to detect and resilient Our evaluation of the defensive techniques used by to blocking or removing. -
Do Not Track a Nokia Browser Look
Do Not Track Nokia Browser Position - Vikram Malaiya Copyright: Nokia Corporation, 2011 Our understanding of Do Not Track (DNT) • DNT is a technology to enables users to opt out of third-party web tracking • No agreed upon definition of DNT. There are currently 3 major technology proposals for responding to third-party privacy concern. 1. Stanford University and Mozilla’s DNT HTTP Header technique. 2. Blacklist based technique such as Microsoft’s ‘Tracking Protection’ which is part of IE9 3. Network Advertising Initiative’s model of a per company opt-out cookie. Opt-out cookie approach is being promoted by Google. DNT as HTTP Header The Browser adds ‘DNT’/ ‘X-Do-Not-Track’ to its http header. The header is sent out to the server with every web request. This header acts as a signal to the server suggesting that the user wishes to opt out of tracking. Adoption: Firefox 4, IE9 DNT as HTTP Header • Pros: – Scope: Server could apply restrictions to all third party entities and tracking mechanisms – Persistent: No reconfiguration needed once set – Simple: Easy to implement on the browser side • Cons: – Only work as long as the server honors users preferences – No way to enforce national regulations/legislations to servers located beyond country boundaries Block(Black) List / Tracking Protection This is a consumer opt-in mechanism which blocks web connections from known tracking domains that are compiled on a list. First party Third party Adoption: ‘Tracking Protection’ in Internet Explorer 9 cy.analytix.com The downloadable Tracking allow Protection Lists enable IE9 xy.ads.com consumers to control what deny third-party site content can deny track them when they’re ads.tracker.com Tracking Protection online. -
Statement of Justin Brookman Director, Consumer Privacy Center for Democracy & Technology Before the U.S. Senate Committee O
Statement of Justin Brookman Director, Consumer Privacy Center for Democracy & Technology Before the U.S. Senate Committee on Commerce, Science, and Transportation Hearing on “A Status Update on the Development of Voluntary Do-Not-Track Standards” April 24, 2013 Chairman Rockefeller, Ranking Member Thune, and Members of the Committee: On behalf of the Center for Democracy & Technology (CDT), I thank you for the opportunity to testify today. We applaud the leadership the Chairman has demonstrated in examining the challenges in developing a consensus Do Not Track standard and appreciate the opportunity to address the continued insufficiency of self-regulatory consumer privacy protections. CDT is a non-profit, public interest organization dedicated to preserving and promoting openness, innovation, and freedom on the decentralized Internet. I currently serve as the Director of CDT’s Consumer Privacy Project. I am also an active participant in the Worldwide Web Consortium’s Tracking Protection Working Group, where I serve as editor of the “Tracking Compliance and Scope” specification — the document that purports to define what Do Not Track should mean. My testimony today will briefly describe the history of online behavioral advertising and the genesis of the Do Not Track initiative. I will then describe the current state of the World Wide Web Consortium’s efforts to create Do Not Track standards and the challenges going forward to implement Do Not Track tools successfully. I will conclude with my thoughts on the future of Do Not Track. and why I believe that this protracted struggle demonstrates the need for the fundamental reform of our nation’s privacy protection framework for commercial and government collection and use of personal information. -
Amazon Silk Developer Guide Amazon Silk Developer Guide
Amazon Silk Developer Guide Amazon Silk Developer Guide Amazon Silk: Developer Guide Copyright © 2015 Amazon Web Services, Inc. and/or its affiliates. All rights reserved. The following are trademarks of Amazon Web Services, Inc.: Amazon, Amazon Web Services Design, AWS, Amazon CloudFront, AWS CloudTrail, AWS CodeDeploy, Amazon Cognito, Amazon DevPay, DynamoDB, ElastiCache, Amazon EC2, Amazon Elastic Compute Cloud, Amazon Glacier, Amazon Kinesis, Kindle, Kindle Fire, AWS Marketplace Design, Mechanical Turk, Amazon Redshift, Amazon Route 53, Amazon S3, Amazon VPC, and Amazon WorkDocs. In addition, Amazon.com graphics, logos, page headers, button icons, scripts, and service names are trademarks, or trade dress of Amazon in the U.S. and/or other countries. Amazon©s trademarks and trade dress may not be used in connection with any product or service that is not Amazon©s, in any manner that is likely to cause confusion among customers, or in any manner that disparages or discredits Amazon. All other trademarks not owned by Amazon are the property of their respective owners, who may or may not be affiliated with, connected to, or sponsored by Amazon. AWS documentation posted on the Alpha server is for internal testing and review purposes only. It is not intended for external customers. Amazon Silk Developer Guide Table of Contents What Is Amazon Silk? .................................................................................................................... 1 Split Browser Architecture ...................................................................................................... -
Understanding Emerging Threats to Online Advertising
Understanding Emerging Threats to Online Advertising Ceren Budak Sharad Goel Justin Rao University of Michigan Stanford University Microsoft Research Georgios Zervas Boston University Questrom School of Business June 11, 2016 Abstract Two recent disruptions to the online advertising market are the widespread use of ad-blocking software and proposed restrictions on third-party tracking, trends that are driven largely by consumer concerns over privacy. Both primarily impact display advertising (as opposed to search and native social ads), and affect how retailers reach customers and how content producers earn revenue. It is, however, unclear what the consequences of these trends are. We investigate using anonymized web browsing his- tories of 14 million individuals, focusing on \retail sessions" in which users visit online sites that sell goods and services. We find that only 3% of retail sessions are initiated by display ads, a figure that is robust to permissive attribution rules and consistent across widely varying market segments. We further estimate the full distribution of how retail sessions are initiated, and find that search advertising is three times more important than display advertising to retailers, and search advertising is itself roughly three times less important than organic web search. Moving to content providers, we find that display ads are shown by 12% of websites, accounting for 32% of their page views; this reliance is concentrated in online publishing (e.g., news outlets) where the rate is 91%. While most consumption is either in the long-tail of websites that do not show ads, or sites like Facebook that show native, first-party ads, moderately sized web publishers account for a substantial fraction of consumption, and we argue that they will be most affected by changes in the display advertising market. -
Commercial Data Privacy and Innovation in the Internet Economy: a Dynamic Policy Framework
COMMERCIAL DATA PRIVACY AND INNOVATION IN THE INTERNET ECONOMY: A DYNAMIC POLICY FRAMEWORK THE DEPARTMENT OF COMMERCE INTERNET POLICY TASK FORCE MESSAGE FROM SECRETARY OF COMMERCE GARY LOCKE The Internet is an extraordinary platform for innovation, economic growth, and social communication. Using the Internet, entrepreneurs reach global markets, political groups organize, and major companies manage their supply chains and deliver services to their customers. Simply stated, the Internet is becoming the central nervous system of our information economy and society. Over the last 15 years, personal computers, mobile phones, and other devices have transformed how we access and use information. As powerful, exciting, and innovative as these developments are, they also bring with them new concerns. New devices and applications allow the collection and use of personal information in ways that, at times, can be contrary to many consumers’ privacy expectations. Addressing these issues in a way that protects the tremendous economic and social value of the Internet without stifling innovation requires a fresh look at Internet policy. For this reason, in April 2010, I launched an Internet Policy Task Force (IPTF), which brings together the technical, policy, trade, and legal expertise of the entire Department. The following report – or green paper – recommends consideration of a new framework for addressing online privacy issues in the United States. It recommends that the U.S. government articulate certain core privacy principles—in order to assure baseline consumer protections—and that, collectively, the government and stakeholders come together to address specific privacy issues as they arise. We believe this framework will both improve the state of affairs domestically and advance interoperability among different privacy regimes around the world so that, globally, Internet services can continue to flourish. -
I Can't Generalize a Whole Lot About the Maxthon Cloud Browser, Which Got
I can’t generalize a whole lot about the Maxthon Cloud Browser, which got a major upgrade to Version 4.x in a December preview and was officially released on February 25. Maxthon Cloud Browser versions are available for Windows, OS X, iOS and Android, and it’s designed to provide users with a seamless and unified user experience across multiple devices and platforms. I can’t speak to the Windows and Android versions, but I’m unevenly impressed with the OS X and iOS variants. I found myself quickly becoming a fan of the OS X version; it’s a lot like Google’s Chrome browser—very fast and slick with super-smooth performance—but more so. It incorporates pretty much everything I like about Chrome, such as an automatic Google Translate machine translation option. The iOS version isn’t bad, just not nearly as outstanding as the OS X version. Interestingly, that would be my assessment of Google Chrome for iOS compared with Chrome for OS X, as well, and I think the reason in both instances is Apple’s imposition on its own WebKit technology on iOS browsers. Using Maxthon Cloud Browser for iOS is not terribly different from the standard iOS Safari experience in terms of speed, but the iOS version of Maxthon has an absolutely maddening bug that sporadically turns the screen brightness on my iPad 2 down to minimum, obliging a trip to the iOS Settings to restore it. I suspect that Maxthon for iOS’s Brightness Control feature that purportedly lets you adjust screen brightness from within the browser, and/or Night Mode that adjusts screen brightness in low light situations are responsible for this behavior. -
Web Tracking: Mechanisms, Implications, and Defenses Tomasz Bujlow, Member, IEEE, Valentín Carela-Español, Josep Solé-Pareta, and Pere Barlet-Ros
ARXIV.ORG DIGITAL LIBRARY 1 Web Tracking: Mechanisms, Implications, and Defenses Tomasz Bujlow, Member, IEEE, Valentín Carela-Español, Josep Solé-Pareta, and Pere Barlet-Ros Abstract—This articles surveys the existing literature on the of ads [1], [2], price discrimination [3], [4], assessing our methods currently used by web services to track the user online as health and mental condition [5], [6], or assessing financial well as their purposes, implications, and possible user’s defenses. credibility [7]–[9]. Apart from that, the data can be accessed A significant majority of reviewed articles and web resources are from years 2012 – 2014. Privacy seems to be the Achilles’ by government agencies and identity thieves. Some affiliate heel of today’s web. Web services make continuous efforts to programs (e.g., pay-per-sale [10]) require tracking to follow obtain as much information as they can about the things we the user from the website where the advertisement is placed search, the sites we visit, the people with who we contact, to the website where the actual purchase is made [11]. and the products we buy. Tracking is usually performed for Personal information in the web can be voluntarily given commercial purposes. We present 5 main groups of methods used for user tracking, which are based on sessions, client by the user (e.g., by filling web forms) or it can be collected storage, client cache, fingerprinting, or yet other approaches. indirectly without their knowledge through the analysis of the A special focus is placed on mechanisms that use web caches, IP headers, HTTP requests, queries in search engines, or even operational caches, and fingerprinting, as they are usually very by using JavaScript and Flash programs embedded in web rich in terms of using various creative methodologies. -
Regulating Online Behavioral Advertising, 44 J. Marshall L. Rev
The John Marshall Law Review Volume 44 | Issue 4 Article 2 Summer 2011 Regulating Online Behavioral Advertising, 44 J. Marshall L. Rev. 899 (2011) Steven C. Bennett Follow this and additional works at: http://repository.jmls.edu/lawreview Part of the Computer Law Commons, Consumer Protection Law Commons, Internet Law Commons, Marketing Law Commons, and the Privacy Law Commons Recommended Citation Steven C. Bennett, Regulating Online Behavioral Advertising, 44 J. Marshall L. Rev. 899 (2011) http://repository.jmls.edu/lawreview/vol44/iss4/2 This Article is brought to you for free and open access by The oJ hn Marshall Institutional Repository. It has been accepted for inclusion in The oJ hn Marshall Law Review by an authorized administrator of The oJ hn Marshall Institutional Repository. REGULATING ONLINE BEHAVIORAL ADVERTISING STEVEN C. BENNETT* Online behavioral advertising ("OBA"), sometimes known as profiling or behavioral targeting, can be used by on-line publishers and internet marketers to increase the efficiency and effectiveness of their advertising campaigns.' OBA works by collecting data on a user's behavior on the Internet including browsing habits, search queries, and web site viewing history. OBA generally seeks to in- crease the relevance of advertising displayed to the user, based on data collected about the user, with the aim of increasing the strength of the connection between advertising efforts and pur- chasing behavior. Recently, the Federal Trade Commission ("FTC"), the De- partment of Commerce ("DOC"), and congressional leaders have suggested a need for more intensive regulation of OBA. The chief objective of such regulation is to ensure that consumer privacy is protected and that abuses of consumer information do not occur. -
It's Not Personal: the Dangers of Misapplied Privacy Policies To
Policy Study 414 March 2013 It’s Not Personal: The Dangers of Misapplied Privacy Policies to Search, Social Media and Other Web Content By Steven Titch Project Director: Julian Morris Reason Foundation Reason Foundation’s mission is to advance a free society by developing, applying and promoting libertarian principles, including individual liberty, free markets and the rule of law. We use journalism and public policy research to influence the frameworks and actions of policymakers, journalists and opinion leaders. Reason Foundation’s nonpartisan public policy research promotes choice, competition and a dynamic market economy as the foundation for human dignity and progress. Reason produces rigorous, peer-reviewed research and directly engages the policy process, seeking strategies that emphasize cooperation, flexibility, local knowledge and results. Through practical and innovative approaches to complex problems, Reason seeks to change the way people think about issues, and promote policies that allow and encourage individu- als and voluntary institutions to flourish. Reason Foundation is a tax-exempt research and education organization as defined under IRS code 501(c)(3). Reason Foundation is supported by voluntary contributions from individuals, foundations and corporations. Copyright © 2013 Reason Foundation. All rights reserved. Reason Foundation It’s Not Personal: The Dangers of Misapplied Privacy Policies to Search, Social Media and Other Web Content By Steven Titch Project Director: Julian Morris Executive Summary Millions of people have come to understand the Internet as a new media platform. For the government, unfortunately, basic comprehension of the business models and consumer demand that drive this platform remains elusive. Traffic and usage statistics show the public is enthusiastically embracing the Internet as a two-way information medium. -
Understanding Emerging Threats to Online Advertising
Understanding Emerging Threats to Online Advertising CEREN BUDAK, University of Michigan SHARAD GOEL, Stanford University JUSTIN RAO, Microsoft Research GEORGIOS ZERVAS, Boston University Questrom School of Business Two recent disruptions to the online advertising market are the widespread use of ad-blocking software and proposed restrictions on third-party tracking, trends that are driven largely by consumer concerns over privacy. Both primarily impact display advertising (as opposed to search and native social ads), and affect how retailers reach customers and how content producers earn revenue. It is, however, unclear what the consequences of these trends are. We investigate using anonymized web browsing histories of 14 million individuals, focusing on “retail sessions” in which users visit online sites that sell goods and services. We find that only 3% of retail sessions are initiated by display ads, a figure that is robust to permissive attribution rules and consistent across widely varying market segments. We further estimate the full distribution of how retail sessions are initiated, and find that search advertising is three times more important than display advertising to retailers, and search advertising is itself roughly three times less important than organic web search. Moving to content providers, we find that display ads are shown by 12% of websites, accounting for 32% of their page views; this reliance is concentrated in online publishing (e.g., news outlets) where the rate is 91%. While most consumption is either in the long-tail of websites that do not show ads, or sites like Facebook that show native, first-party ads, moderately sized web publishers account for a substantial fraction of consumption, and we argue that they will be most affected by changes in the display advertising market. -
Web-Browsing History
Mag. iur. Dr. techn. Michael Sonntag Web-browsing history Institute for Information Processing and Microprocessor Technology (FIM) Johannes Kepler University Linz, Austria E-Mail: [email protected] http://www.fim.uni-linz.ac.at/staff/sonntag.htm © Michael Sonntag 2013 Agenda The elements of web-browsing history and intentionality HTTP – Hypertext Transfer Protocol Cookies Internet Explorer File locations The index.dat file format Example Date/Time formats Firefox File locations Cookies, history, cache Webmail reconstruction example Michael Sonntag Web-browsing history 2 The elements of web-browsing history History The list of URLs visited (at which time, …) Provides general information on time and location of activity » URL's may also contain information: GET requests – Example: Google searches Cookies Which websites were visited when + additional information May allow determining whether the user was logged in Can survive much longer than the history » Depends on the expiry date of the Cookie and the configuration Cache The content of the pages visited » Incomplete: E.g. ad's will rarely be cached (No-cache headers) Provides the full content of what was seen, e.g. Webmail » More exactly: What was delivered by the server Michael Sonntag Web-browsing history 3 Web-browsing history: Intentionality Did the user visit the webpage intentionally? In general: If it's in the cache/history/cookie file: Yes See also: Bookmarks! BUT: What about pop-ups? » E.g.: Pornography ads (no one sees them intentionally )! Password protected pages? » But images/JavaScript can easily supply passwords as well when opening a file! Investigation of other files, trying it out, content inspection … needed to verify, whether a page that was visited, was actually intended to be visited (“intentionality”) Usually this should not be a problem: » Logging in to the mail » Visiting a website after entering log-ins Michael Sonntag » Downloading files Web-browsing history 4 Web browsing procedure 1.