Privacy tools fail to stop harms from real-world data misuse
Enhancing Privacy, Neglecting Harms: An Analysis of Real-World Digital Privacy Incidents
Cryptography and SecurityComputers and Society
Summary
Digital privacy tools are designed to give people more control over their personal information, but privacy harms still happen. The researchers studied 257 real privacy incidents reported in the news to understand why privacy protections often fall short. They built a new model showing that privacy harms come from complex interactions between many parties and that simply getting consent doesn’t stop violations. They also found that those who could best prevent harm often lack the motivation to do so, which limits how well current privacy technologies can protect people.
What this means in practice
- •For privacy compliance teams: Improve incident response by using the new model to identify complex data interactions and pinpoint where harms emerge in real-world privacy breaches.
- •For data protection officers: Design better privacy policies that go beyond consent to address how harms develop across multiple stakeholders and actions in data processing.
Authors
Shannon Veitch, C. Shem, Lena Csomor, Oleksandr Dudiy, Naone Kim, Khoi Le, Lina Saha, Alexander Viand, Anwar Hithnawi, Bailey Kacsmar
Abstract
Privacy-enhancing technologies (PETs) have emerged as a technical means for providing individuals with greater control over their information. Yet despite the growing deployment of PETs, people continue to experience privacy harms. In this work, we revisit our understanding of privacy incidents and the realities of those experiencing privacy harms, to assess whether the goals and abilities of PETs are misaligned with the harms people face. For our study, we collect news articles that correspond to a sample of 257 real-world privacy incidents. We employ content analysis over the articles to develop a new information flow model that encompasses the complexity of data flows and their relation to resulting harms. We demonstrate that our model captures both established and novel aspects of privacy incidents and their mitigations. In particular, it captures why consent is often insufficient to prevent privacy violations, how harms emerge from complex interactions among multiple entities and actions, and reveals a flaw in our understanding of PETs: a focus on enabling functionalities still permits the harms inherent in those functionalities. Moreover, we find that the entities best positioned to implement harm-preventing measures for the incidents in our sample are the least incentivized to do so. Overall, our model and analysis identify limitations of privacy technology research for harm prevention and further identifies paths for transforming how we approach the advancement of these technologies.