Emerging Researchers National (ERN) Conference

nsf-logo[1]

Web Privacy Census: Cookies and HTML5 Double as Flash Fades

Undergraduate #197
Discipline: Computer Sciences and Information Management
Subcategory: Computer Science & Information Systems

Jade Seymore - Bethune-Cookman University
Co-Author(s): Luis Mojica and Nathan Good, University of California Berkeley, Berkeley, CA Ibrahim Altaweel, University of Santa Cruz, Santa Cruz, CA David Garcia, Southwestern College, Chula Vista, CA


The Web Privacy Census aimed to increase public policymakers awareness of web tracking with data to support the idea of increasing measures to give more consumers privacy online. As policymakers consider different approaches for addressing Internet privacy, it is critical to understand how interventions such as negative press attention, self-regulation, Federal Trade Commission enforcement, and direct regulation affect tracking.We seek to explore: How many entities are tracking users online? What website categories have the most cookies placed on a single visit? Continuing on from previous studies, here we report on the state of Internet tracking on the most popular websites. Data were collected on the United States top 100, 1000 and 25,000 websites as ranked on Quantcast’s top 1 million websites in the United States using a crawler. HTTP Cookies and HTML5 Local Storage doubled since the 2012 report. There were over one million HTTP Cookies collected from the top 25,000 Quantcast U.S. websites. We saw an expected decrease in the number of websites using Flash Cookies in the 2015 report. Since the 2012 report, we also noted a growth in alternative methods that trackers have utilized to gather information from unsuspecting users on the Internet. Here we compare data with the 2012 Web Privacy Census and discuss the patterns and trends we see surrounding the current state of web privacy. We predict that we will see more adoption of fingerprinting methods. In the future we hope to collect and show what websites track users using the fingerprint tracking method.

Funder Acknowledgement(s): National Science Foundation (NSF award number CCF-0424422)

Faculty Advisor: Nathan Good,

nsf-logo[1]

This material is based upon work supported by the National Science Foundation (NSF) under Grant No. DUE-1930047. Any opinions, findings, interpretations, conclusions or recommendations expressed in this material are those of its authors and do not represent the views of the AAAS Board of Directors, the Council of AAAS, AAAS’ membership or the National Science Foundation.