The Struggle for WHOIS Privacy: Understanding the Standoff Between ICANN and the World's Data Protection Authorities
Bibliographic record
Abstract
This dissertation examines the struggle over privacy rights in WHOIS, the public directory of registrants of Internet domain names. ICANN, the Internet Corporation for Assigned Names and Numbers, is the non-profit corporation established by the U.S. government to run the Domain Name System and the Internet Assigned Numbers Authority, functions essential for Internet operations. Through contractual obligation, ICANN requires registrars to collect and publish personal data in the WHOIS directory, contravening many national data protection laws. My research first asked how ICANN managed to avoid the demands of authorities mandated to enforce data protection laws. Analyzing extensive documentary records maintained by ICANN, I demonstrate that the organization refused to effectively accommodate privacy concerns in their policies. I found that, since its inception, ICANN rebuffed repeated complaints by data protection authorities that WHOIS requirements violate national laws and continue to avoid privacy compliance. I provide evidence of a clash of values in the emerging commercial Internet. Business enterprises with strong intellectual property interests, supported by the U.S. government, initiated the focus on an open WHOIS policy to ensure they could identify suspected copyright and trademark violators. Law enforcement agencies represented at ICANN’s Governmental Advisory Committee also demanded open access to registrant data. A growing information services industry depended on the sale of this data to domain businesses and cybercrime fighters in both the public and private sectors. In combination, these stakeholders have prevented privacy advocates from gaining a foothold. Data Protection Authorities have also declined to exercise their powers, and they have remained outsiders and unsuccessful interveners in ICANN’s multi-stakeholder process. The dissertation then explores the implications of this failure of privacy law from the perspectives of Internet privacy scholarship and accountability issues in multi-stakeholder governance. Establishing WHOIS as a wide-open information resource not only erodes legitimate expectations of privacy in telecommunications directories, it undermines our ability to negotiate personal space and speech on the Internet. This research contributes to understanding challenges to Internet privacy, law enforcement access to personal data, and the prospects for developing international Internet governance regimes that promote the public interest while protecting the rights of individuals.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.021 | 0.005 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".