Tootfinder

Human-Centered Interactive Anonymization for Privacy-Preserving Machine Learning: A Case for Human-Guided k-Anonymity
Sri Harsha Gajavalli
https://arxiv.org/abs/2507.04104

Human-Centered Interactive Anonymization for Privacy-Preserving Machine Learning: A Case for Human-Guided k-Anonymity
Privacy-preserving machine learning (ML) seeks to balance data utility and privacy, especially as regulations like the GDPR mandate the anonymization of personal data for ML applications. Conventional anonymization approaches often reduce data utility due to indiscriminate generalization or suppression of data attributes. In this study, we propose an interactive approach that incorporates human input into the k-anonymization process, enabling domain experts to guide attribute preservation based…

Geldschein-Verfolgung: Zunehmendes Bargeld-Tracking besorgt Datenschützer
Wenn Seriennummern von Scheinen mit Zeit und Ort der Erfassung gespeichert und diese Daten verstärkt gesammelt werden, geht die Anonymität des Bargelds flöten.

Millions of public euros subsidize bullfighting through regional televisions https://www.animanaturalis.org/n/46882?utm_source=Mastodon
Madrid raises its voice against bullfighting and for a cruelty-free culture

Millions of public euros subsidize bullfighting through regional televisions
We reveal the hidden cost of public funding for bullfighting broadcasts on Spain’s regional television channels, which has increased in recent years, especially in those Autonomous Communities governed by the Partido Popular and VOX.

facebook_friends: Maier Facebook friends (2014)
A small anonymized Facebook ego network, from April 2014. Nodes are Facebook profiles, and an edge exists if the two profiles are "friends" on Facebook. Metadata gives the social context for the relationship between ego and alter.
This network has 362 nodes and 1988 edges.
Tags: Social, Online, Unweighted, Metadata

Attention les yeux ! Première analyse "en direct" d'une solution "en double anonymat" qui fait sa pub sur Linkedin, pour vérifier l'age des personnes accédant Š un site pornographique : AnonymAge !
On rappelle que le double anonymat, c'est que le site porno n'apprend pas l'identité de l'utilisateurice et l'application de vérification n'apprend pas le site visité.
Deuxième étape de la vérification : on prend son téléphone, on lan…

Breaking Anonymity at Scale: Re-identifying the Trajectories of 100K Real Users in Japan
Abhishek Kumar Mishra, Mathieu Cunche, Heber H. Arcolezi
https://arxiv.org/abs/2506.05611 …

Breaking Anonymity at Scale: Re-identifying the Trajectories of 100K Real Users in Japan
Mobility traces represent a critical class of personal data, often subjected to privacy-preserving transformations before public release. In this study, we analyze the anonymized Yjmob100k dataset, which captures the trajectories of 100,000 users in Japan, and demonstrate how existing anonymization techniques fail to protect their sensitive attributes. We leverage population density patterns, structural correlations, and temporal activity profiles to re-identify the dataset's real-world locatio…

darum zahl ich alles nur noch mit münzen
https://netzpolitik.org/2025/bargeld-tracking-du-hast-ueberwachungsinstrumente-im-portemonnaie/

The invisible agony of fish in Spain's fish farms #AnimalRights

The invisible agony of fish in Spain's fish farms
Spain is the leading aquaculture producer in the European Union, resulting in over 254 million fish bred and slaughtered annually in industrial fish farms. Yet these animals lack real protection, as revealed by our latest investigation.

Demand that the European Union does not leave millions of dogs and cats unprotected against illegal breeding! #AnimalRights

Demand that the European Union does not leave millions of dogs and cats unprotected against illegal breeding!
While MEPs prepare to vote on a groundbreaking regulation on the welfare of dogs and cats, animal welfare organizations warn: the proposed exemptions could leave millions of animals unprotected.

The Impact of Event Data Partitioning on Privacy-aware Process Discovery
Jungeun Lim, Stephan A. Fahrenkrog-Petersen, Xixi Lu, Jan Mendling, Minseok Song
https://arxiv.org/abs/2507.06008

The Impact of Event Data Partitioning on Privacy-aware Process Discovery
Information systems support the execution of business processes. The event logs of these executions generally contain sensitive information about customers, patients, and employees. The corresponding privacy challenges can be addressed by anonymizing the event logs while still retaining utility for process discovery. However, trading off utility and privacy is difficult: the higher the complexity of event log, the higher the loss of utility by anonymization. In this work, we propose a pipeline …