Big Friend is Watching You: Analyzing Online Social Networks Tracking Capabilities | Chaabane, Kaafar, Boreli

Abdelberi Chaabane, Mohamed Ali Kaafar (INRIA), Roksana Boreli (NSW, AU); Big Friend is Watching You: Analyzing Online Social Networks Tracking Capabilities; In Proceedings of the Workshop on Online Social Networks (WOSN); 2012-08-17; 6 pages.
tl;dr → there be dragons, there might be harms; Facebook is bad; they used Ghostery to sample & catalog.  Does not mention mitigations or a consent model.

Abstract

In this paper, we examine web user tracking capabilities of the three major global Online Social Networks (OSNs). We study the mechanisms which enable these services to persistently and accurately follow users web activity, and evaluate to which extent this phenomena is spread across the web. Through a study of the top 10K websites, our findings indicate that OSN tracking is diffused among almost all website categories, independently from the content and from the audience. We also evaluate the tracking capabilities in practice and demonstrate by analyzing a real traffic traces that OSNs can reconstruct a significant portion of users web profile and browsing history. We finally provide insights into the relation between the browsing history characteristics and the OSN tracking potential, highlighting the high risk properties.

Mentions

  • <quote>We used a modified version of Ghostery [1] to tag tracking and
    ad companies.</quote>
  • beacons, pixels, cookies
  • personalization
  • content targeting

Generators

monitoring the consumer.

  • Facebook
  • Google+
  • Twitter

Receivers

receiving & using consumer datums.

  • AOL
  • Google AdSense
  • Microsoft
  • Yahoo yieldmanager

Beware the bots: Some best practices to combat the fraudulent traffic industry | Nieman Lab

Original Sources

Bot Benchmark Report: What Makes a Publisher Premium; White Ops, commissioned by Digital Content Next (DCN); 2015-09; 32 pages.
tl;dr → 32 publishers. <quote>DCN didn’t name the specific publishers in the study, but it considers its members “premium” publishers — think big brands like ABC, The New York Times, and National Geographic.</quote>

The Bot Baseline: Fraud In Digital Advertising; White Ops, commissioned by the Association of National Advertisers (ANA); 2014-12; 57 pages; press release; landing.
tl;dr → <quote>White Ops, which left out the names of the advertiser and website in its published study, declined to comment [on the report]</quote>.

Mentions

  • <quote>Bot rates appear to be tied to publishers’ own audience development and traffic-sourcing policies, the study found. Practices such as selling data to third parties or purchasing traffic from outside vendors were associated with those publishers showing higher bot rates. Notable, also, is the finding that publishers with less overall traffic were more likely to have higher sophisticated bot rates.</quote>

Quoted

For color, background & verisimilitude

  • Jason Kint, CEO, Digital Content Next (DCN)

Actualities

The Ad Blocking Controversy, Explained | Brian O’Kelley

Brian O’Kelley (AppNexus); The Ad Blocking Controversy, Explained; In Forbes; 2015-09-23.

tl;dr → ad blockers reduce viable inventory; this reduces supply; it willmight increase prices.

Mentions

  • it will be interesting times.

Referenced

How to Build a Content Farm in 20 Minutes | Carles (Carlos Perez), Motherboard

How to Build a Content Farm in 20 Minutes; Carles (Carlos Perez); In Motherboard; 2015-09-25.
Teaser: How Much of Your Audience is Fake? As Much as Inhumanly Possible

Responsive To

How Much of Your Audience is Fake?; Ben Elgin, Michael Riley, David Kocieniewski, and Joshua Brustein; In Bloomberg Business; 2015-09-23; separately noted.
Teaser: Marketers thought the Web would allow perfectly targeted ads. Hasn’t worked out that way.

Mentions

  • <quote>However, everything trackable is all just data fields that can easily be populated to game traffic auditors, or your own computer can be taken over by malware.</quote>
  • <quote>It’s hard to see programmatic advertising as anything other than the most complex, and highly profitable remnant inventory scheme.</quote>
  • big box content farms
    • aggregate
    • sources
      • social
      • search
      • email
  • Comcast data
  • <quote>When a media company is acquired, does the acquirer see fake, cheap traffic as part of the value, or a misleading element of inflated value? Pumping and dumping media companies is easier than ever.</quote>
  • <quote>We all must realize that clickbait is not the problem. It’s only a standard tool in the broken economy of traffic jacking. </quote>
  • <quote>When I’m browsing the internet, I usually realize that I am on a low quality site if programmatic ads are following me around. Somehow, I’ve navigated the the farthest reaches of the internet that is serving the cheapest ads to the longtailiest users who may be influenced by them. Programmatic ads means that you are in no-man’s land, where publishers weren’t integrated into native, social, and live programmed events.</quote>
  • <quote>There is no way for the reader to stand up for themselves because even if you chose not to read, a robot will take your place.</quote>

Adblockers: The Only Way Out | Monday Note

Frederic Filloux; Adblockers: The Only Way Out; In His Blog entitled Monday Note; 2015-09-27.

tl;dr → it’s going to get worse before it gets better

Mentions

  • Factoids are recited
  • The suggested response

Listicle

  1. Acceptable ads will be defined.
  2. Low-end formats will disappear
  3. Paid-for models for news will rise
  4. Micropayments.

Wait, what? Mobile browser traffic is 2X bigger than app traffic, and growing faster | VentuireBeat

Wait, what? Mobile browser traffic is 2X bigger than app traffic, and growing faster; ; In VentureBeat; 2015-09-25.

tl;dr → two industry booster reports contradict each other; which is correct? Both!  VentureBeat has a paywalled report too!

Original Sources

Can Online Display Advertising Attract New Customers? | Lewis, Reiley, Schreiner

Randall A. Lewis (MIT), David H. Reiley (Yahoo), Taylor A. Schreiner (Yahoo); Can Online Display Advertising Attract New Customers?; In Some Venue; 2009-01-16 → 2010-01-18; 18 pages.
Teaser: Measuring an Advertiser’s New Accounts with a Large-Scale Experiment on Yahoo!

Abstract

A large-scale experiment involving 3.7 million treated subjects on Yahoo tests the ability of online display advertising to attract new customers. We track the number of new account sign-ups at an online business and demonstrate a statistically significant impact of one of the two types of advertising campaigns. We find that the ads shown on Yahoo Mail did not produce a statistically significant increase in sign-ups. Despite being derived using millions of subjects, this estimate is quite noisy, with the upper bound of the 95% confidence interval estimate being a 15% increase in new customers. By contrast, the ads served as Yahoo Run-of Network succeeded in generating a more precise and statistically significant increase in sign-ups of 8-14% relative to the control group. These figures call into question click-only attribution models, as the number of users that clicked on an ad and converted is less than 30% of the estimated treatment effect. Further, it is likely that many ad clickers would have converted in the absence of the ads, a likely possibility ignored by traditional click-attribution models.

It’s Time to Flip the Bit on Publishing and Data | John Battelle

John Battelle; It’s Time to Flip the Bit on Publishing and Data; In His Blog; 2015-09-27.

tl;dr → all talking heads, all of them; let’s compete on innovation!

Mentions

  • Factoids are recited
    • Bloomberg;
  • Pundits are quoted
    • Clayton Christiansen
    • Cory Doctorow
    • Frederic Filloux
    • Tim O’Reilly
    • Michael Schrage
    • Doc Searls

Referenced

  • How Much of Your Audience is Fake?; Ben Elgin, Michael Riley, David Kocieniewski, and Joshua Brustein; In Bloomberg Business; 2015-09-23; separately noted.
    Teaser: Marketers thought the Web would allow perfectly targeted ads. Hasn’t worked out that way.

Cookies Lack Integrity: Real-World Implications | Zheng, Jiang, Liang, Duan, Chen, Wan, Weaver

Zheng, et al.; Cookies Lack Integrity: Real-World Implications; In Proceedings of the 25th USENIX Security Symposium; 2015-08-13; landing.

Authors

  • Xiaofeng Zheng, Tsinghua University and Tsinghua National Laboratory for Information Science and Technology
  • Jian Jiang, University of California, Berkeley
  • Jinjin Liang, Tsinghua University and Tsinghua National Laboratory for Information Science and Technology
  • Haixin Duan, Tsinghua University, Tsinghua National Laboratory for Information Science and Technology, and International Computer Science Institute
  • Shuo Chen, Microsoft Research Redmond
  • Tao Wan, Huawei Canada
  • Nicholas Weaver, International Computer Science Institute and University of California, Berkeley

Revisions

Abstract

A cookie can contain a “secure” flag, indicating that it should be only sent over an HTTPS connection. Yet there is no corresponding flag to indicate how a cookie was set: attackers who act as a man-in-the-middle even temporarily on an HTTP session can inject cookies which will be attached to subsequent HTTPS connections. Similar attacks can also be launched by a web attacker from a related domain. Although an acknowledged threat, it has not yet been studied thoroughly. This paper aims to fill this gap with an in-depth empirical assessment of cookie injection attacks. We find that cookie-related vulnerabilities are present in important sites (such as Google and Bank of America), and can be made worse by the implementation weaknesses we discovered in major web browsers (such as Chrome, Firefox, and Safari). Our successful attacks have included privacy violation, online victimization, and even financial loss and account hijacking. We also discuss mitigation strategies such as HSTS, possible browser changes, and present a proof-of-concept browser extension to provide better cookie isolation between HTTP and HTTPS, and between related domains.

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