Tootfinder

Annual DC Privacy Forum: Convening Top Voices in Governance in the Digital Age
https://fpf.org/blog/annual-dc-privacy-forum-convening-top-voices-in-governance-in-the-digital-age/
@…

Kein Linkverbot, keine Provision: Apple verliert Kontrolle über den App Store
Strikte Regeln für App-Anbieter sicherten Apple Milliardenumsätze mit Provisionen. In den USA und in der EU sind diese nicht länger erlaubt.

heise | Günstige PV-Module per Gebrauchtmarkt: Perfekt für Bastler, riskant für Dächer
Secondhand statt neu: Auch bei Solarmodulen ist das möglich. Der Kauf lohnt sich aber nur für bestimmte Projekte und ist nicht ohne Risiko.

Internet exploitation and abuse of children is a unique category of online crime and therefore cannot be used lightly by any side in debates around regulation of online privacy tools.
https://theprivacydad.com/privacy-tools-vs-online-child-exploitat…

#privacy

How to Disappear: Secrets of the World’s Greatest Privacy Experts
Inside the world of extreme-privacy consultants, who, for the right fee, will make you and your personal information very hard to find

Don't Hash Me Like That: Exposing and Mitigating Hash-Induced Unfairness in Local Differential Privacy
Berkay Kemal Balioglu, Alireza Khodaie, Mehmet Emre Gursoy
https://arxiv.org/abs/2506.20290

Don't Hash Me Like That: Exposing and Mitigating Hash-Induced Unfairness in Local Differential Privacy
Local differential privacy (LDP) has become a widely accepted framework for privacy-preserving data collection. In LDP, many protocols rely on hash functions to implement user-side encoding and perturbation. However, the security and privacy implications of hash function selection have not been previously investigated. In this paper, we expose that the hash functions may act as a source of unfairness in LDP protocols. We show that although users operate under the same protocol and privacy budge…

So, the Gemini stuff pissed me off enough to disable updates on my phone, but now it looks like I'm overreacting
https://www.engadget.com/ai/what-do-googles-gemini-privacy-changes-actually-mean-200819778.html
Except I don…

What do Google's Gemini privacy changes actually mean?
An email sent to the AI chatbot users made waves in the tech press.

Mediator Proposes $20 Million Settlement in Trump's CBS Suit (Wall Street Journal)
https://www.wsj.com/business/media/mediator-proposes-20-million-settlement-in-trumps-cbs-suit-ed04c3e3?st=KHicGt&reflink=desktopwebshare_permalink
http://www.memeorandum.com/250625/p112#a250625p112

Machine Learning with Privacy for Protected Attributes
Saeed Mahloujifar, Chuan Guo, G. Edward Suh, Kamalika Chaudhuri
https://arxiv.org/abs/2506.19836 htt…

Machine Learning with Privacy for Protected Attributes
Differential privacy (DP) has become the standard for private data analysis. Certain machine learning applications only require privacy protection for specific protected attributes. Using naive variants of differential privacy in such use cases can result in unnecessary degradation of utility. In this work, we refine the definition of DP to create a more general and flexible framework that we call feature differential privacy (FDP). Our definition is simulation-based and allows for both additio…

PrivacyXray: Detecting Privacy Breaches in LLMs through Semantic Consistency and Probability Certainty
Jinwen He, Yiyang Lu, Zijin Lin, Kai Chen, Yue Zhao
https://arxiv.org/abs/2506.19563

PrivacyXray: Detecting Privacy Breaches in LLMs through Semantic Consistency and Probability Certainty
Large Language Models (LLMs) are widely used in sensitive domains, including healthcare, finance, and legal services, raising concerns about potential private information leaks during inference. Privacy extraction attacks, such as jailbreaking, expose vulnerabilities in LLMs by crafting inputs that force the models to output sensitive information. However, these attacks cannot verify whether the extracted private information is accurate, as no public datasets exist for cross-validation, leaving…