De-Anonymizing Web Browsing Data with Social Networks | Su, Shukla, Goel, Narayanan

Jessica Su, Ansh Shukla, Sharad Goel, Arvind Narayanan; De-Anonymizing Web Browsing Data with Social Networks; draft; In Some Venue Surely (they will publish this somewhere, it is so very nicely formatted); 2017-05; 9 pages.

Abstract

Can online trackers and network adversaries de-anonymize web browsing data readily available to them? We show—theoretically, via simulation, and through experiments on real user data—that de-identified web browsing histories can be linked to social media profiles using only publicly available data. Our approach is based on a simple observation: each person has a distinctive social network, and thus the set of links appearing in one’s feed is unique. Assuming users visit links in their feed with higher probability than a random user, browsing histories contain tell-tale marks of identity. We formalize this intuition by specifying a model of web browsing behavior and then deriving the maximum likelihood estimate of a user’s social profile. We evaluate this strategy on simulated browsing histories, and show that given a history with 30 links originating from Twitter, we can deduce the corresponding Twitter profile more than 50% of the time. To gauge the real-world effectiveness of this approach, we recruited nearly 400 people to donate their web browsing histories, and we were able to correctly identify more than 70% of them. We further show that several online trackers are embedded on sufficiently many websites to carry out this attack with high accuracy. Our theoretical contribution applies to any type of transactional data and is robust to noisy observations, generalizing a wide range of previous de-anonymization attacks. Finally, since our attack attempts to find the correct Twitter profile out of over 300 million candidates, it is—to our knowledge—the largest-scale demonstrated de-anonymization to date.

Promotions

  • Ad Networks Can Personally Identify Web Users; Wendy Davis; In MediaPost; 2017-01-20.
    <quote> The authors tested their theory by recruiting 400 people who allowed their Web browsing histories to be tracked, and then comparing the sites they visited to sites mentioned in Twitter accounts they followed. The researchers say they were able to use that method to identify more than 70% of the volunteers.</quote>

The Real Roots of Midlife Crisis are in the U-Curve | The Atlantic

The Real Roots of Midlife Crisis; Jonathan Rauch; In The Atlantic; 2014-12.
Teaser: What a growing body of research reveals about the biology of human happiness—and how to navigate the (temporary) slump in middle age

Jonathan Rauch is

  • a contributing editor of The Atlantic
  • a contributing editor of the National Journal
  • a senior fellow at the Brookings Institution.

tl;dr → 6200 words; the U-Curve, the happiness U-curve, happiness economics, wisdom research.

Separately noted.

The Organization Kid | David Brooks (2001)

The Organization Kid; David Brooks; In The Atlantic; 2001-04.
Teaser: The young men and women of America’s future elite work their laptops to the bone, rarely question authority, and happily accept their positions at the top of the heap as part of the natural order of life.

tl;dr → 13,000 words

Sections

  • (Introduction)
  • The Origins of the Organization Kid
  • The Moral Life of the Organization Kid
  • “Love and Success and Being Happy”
  • (Wrapup)

Separately noted.

My Experiment Opting Out of Big Data Made Me Look Like a Criminal | TIME

My Experiment Opting Out of Big Data Made Me Look Like a Criminal; Janet Vertesi; In TIME; 2014-05-01.
Teaser: Here’s what happened when I tried to hide my pregnancy from the Internet and marketing companies.
Janet Vertesi is Assistant Professor of Sociology at Princeton University, where she is a Faculty Fellow at the Center for Information Technology Policy.

tl;dr => performance art & street theater for the lulz; she was not harmed, inconvenienced, or even embarassed really… except at her own hand.

Original Sources

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