Tales from the Dark Side: Privacy Dark Strategies and Privacy Dark Patterns

By Christoph Bösch, Benjamin Erb, Frank Kargl, Henning Kopp, Stefan Pfattheicher. Proceedings on Privacy Enhancing Technologies, 2016

325 citations recorded by the source corpus.

Abstract Privacy strategies and privacy patterns are fundamental concepts of the privacy-by-design engineering approach. While they support a privacy-aware development process for IT systems, the concepts used by malicious, privacy-threatening parties are generally less understood and known. We argue that understanding the “dark side”, namely how personal data is abused, is of equal importance. In this paper, we introduce the concept of privacy dark strategies and privacy dark patterns and present a framework that collects, documents, and analyzes such malicious concepts. In addition, we investigate from a psychological perspective why privacy dark strategies are effective. The resulting framework allows for a better understanding of these dark concepts, fosters awareness, and supports the development of countermeasures. We aim to contribute to an easier detection and successive removal of such approaches from the Internet to the benefit of its users.

Subfields: Information Systems, Sociology and Political Science, Human-Computer Interaction

View Paper: https://www.semanticscholar.org/paper/9057b32207e08598d685efed4d1a9cd4ca83b817

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Citations in the corpus

Dark Patterns after the GDPR: Scraping Consent Pop-ups and Demonstrating their Influence (2020, background): “The practice of dark patterns for privacy notices — while only sometimes discussed under this moniker in HCI and privacy literature [9, 15, 29, 38] — is extensively reported on by consumer protection organisations [28], white papers [49], and popular press [47] (for an excellent overview, see the No”
Opt out of privacy or "go home": understanding reluctant privacy behaviours through the FoMO-centric design paradigm (2019, background): “[14] adopt Kahneman’s [40] language of “System 1” (automatic, unconscious) and “System 2” (deliberate, conscious) thinking, saying that”
Dark Patterns at Scale (2019, methodology): “First, while prior work has largely focused on creating taxonomies of the types of dark patterns either based on anecdotal data [31, 32] or data collected from users’ submissions [38, 48], we provide large-scale evidence documenting the presence and prevalence of dark patterns in the wild.”
What Makes a Dark Pattern... Dark?: Design Attributes, Normative Considerations, and Measurement Methods (2021, background): “[4] introduced a set of seven privacy dark patterns, including Bad Defaults, where “the default options are sometimes chosen badly in the sense that they ease or encourage the sharing of personal information.”
Nudges for Privacy and Security (2017, background): “For example, Brandimarte et al. [2013] found a control paradox in the responses of users deciding to whether to share personal data. When the presentation introduced sources of uncertainty about whether their profile would be published online, the users revealed less sensitive information than users”