Doxing: a conceptual analysis

By David Michael Douglas. 2016

180 citations recorded by the source corpus.

Doxing is the intentional public release onto the Internet of personal information about an individual by a third party, often with the intent to humiliate, threaten, intimidate, or punish the identified individual. In this paper I present a conceptual analysis of the practice of doxing and how it differs from other forms of privacy violation. I distinguish between three types of doxing: deanonymizing doxing, where personal information establishing the identity of a formerly anonymous individual is released; targeting doxing, that discloses personal information that reveals specific details of an individual’s circumstances that are usually private, obscure, or obfuscated; and delegitimizing doxing, which reveals intimate personal information that damages the credibility of that individual. I also describe how doxing differs from blackmail and defamation. I argue that doxing may be justified in cases where it reveals wrongdoing (such as deception), but only if the information released is necessary to reveal that such wrongdoing has occurred and if it is in the public interest to reveal such wrongdoing. Revealing additional information, such as that which allows an individual to be targeted for harassment and intimidation, is unjustified. I illustrate my discussion with the examples of the alleged identification of the creator of Bitcoin, Satoshi Nakamoto, by Newsweek magazine, the identification of the notorious Reddit user Violentacrez by the blog Gawker, and the harassment of game developer Zoe Quinn in the ‘GamerGate’ Internet campaign.

Subfields: Clinical Psychology, Privacy & Security, AI Ethics, Fairness & Society

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Clinical Psychology

1. Abeba Birhane

In Privacy & Security

1. Thomas Ristenpart
2. Borja Balle
3. T. Stepleton
4. Peter Kairouz
5. Aurélien Bellet
6. Badih Ghazi
7. Yu-Xiang Wang

In AI Ethics, Fairness & Society

1. William S. Isaac
2. Iason Gabriel
3. Kathryn Henne
4. Karen E. C. Levy
5. Andrew Smart
6. Thomas Ristenpart
7. Borja Balle
8. P. Nicholas

Citations in the corpus

• Taxonomy of Risks posed by Language Models (2022, background): “Disclosure of private information can have the same effects as doxing (the publication of private or identifying information about an individual with malicious intent), causing psychological and material harm [51, 119, 181].”
• “A Stalker's Paradise”: How Intimate Partner Abusers Exploit Technology (2018, background): “Other well-studied types of technology-enabled abuse include online harassment [22,47,51], doxxing [5,15], cyberbullying [2,14], and cyberstalking [17,20,38].”
• Sociotechnical Harms: Scoping a Taxonomy for Harm Reduction (2022, background): “Beyond gender violence, other facets of technology-facilitated violence, include doxxing [69], trolling [14], cyberstalking [14], cyberbullying [14, 88, 179], monitoring and con-trol [38], and online harassment and intimidation [88, 169, 174, 200], under the broader banner of online toxicity [88,…”
• Sociotechnical Harms of Algorithmic Systems: Scoping a Taxonomy for Harm Reduction (2022, background): “Beyond gender violence, other facets of technology-facilitated violence, include doxxing [79], trolling [14], cyberstalking [14], cyberbullying [14, 98, 204], monitoring and control [44], and online harassment and intimidation [98, 192, 199, 226], under the broader banner of online toxicity [98,…”