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…

Insider: Großer russischer Vergeltungsschlag steht noch aus
Insidern zufolge ist Putins angedrohter Vergeltungsschlag gegen die Ukraine noch nicht wirklich erfolgt. Der Zeitpunkt der vollständigen russischen Reaktion sei unklar, werde aber innerhalb weniger Tage erwartet, sagte ein US-Regierungsmitarbeiter, der anonym bleiben wollte, gegenüber der Nachrichtenagentur Reuters. Der Angriff werde wahrscheinlich verschiedene Arten…
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Ukraine-Liveblog: ++ Selenskyj: Putin will totale Niederlage der Ukraine ++
Kremlchef Putin ist nach Meinung des ukrainischen Präsidenten Selenskyj nicht an einem Waffenstillstand interessiert. Bei russischen Angriffen wurde nach ukrainischen Angaben in der Region Dnipropetrowsk mindestens ein Mensch getötet. Der Liveblog vom Sonntag zum Nachlesen.

ich bin unter meinem „Klarnamen“¹ öffentlich dagegen, daß die Union andere² verpflichten will, unter ihrem „Klarnamen“¹ zu agieren. Anonyme wie pseudonyme Kommunikation – nicht nur in privaten Chatgruppen sondern auch gegenüber einer nicht klar gestimmten „Öffentlichkeit“ – ist wichtig. Ein Namenszwang schützt überhaupt nicht gegen die ganze Scheiße, die im Netz passiert.
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¹da geht es um das Ding, das im Perso steht
²und mich

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…

Best-of-N through the Smoothing Lens: KL Divergence and Regret Analysis
Gholamali Aminian, Idan Shenfeld, Amir R. Asadi, Ahmad Beirami, Youssef Mroueh
https://arxiv.org/abs/2507.05913

Best-of-N through the Smoothing Lens: KL Divergence and Regret Analysis
A simple yet effective method for inference-time alignment of generative models is Best-of-$N$ (BoN), where $N$ outcomes are sampled from a reference policy, evaluated using a proxy reward model, and the highest-scoring one is selected. While prior work argues that BoN is almost optimal in reward vs KL tradeoffs, the effectiveness of BoN depends critically on the quality of the proxy reward model used for selection. For this purpose, we study BoN through a smooth version known as Soft Best-of-N…

This https://arxiv.org/abs/2506.00100 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCY_…

Children's Voice Privacy: First Steps And Emerging Challenges
Children are one of the most under-represented groups in speech technologies, as well as one of the most vulnerable in terms of privacy. Despite this, anonymization techniques targeting this population have received little attention. In this study, we seek to bridge this gap, and establish a baseline for the use of voice anonymization techniques designed for adult speech when applied to children's voices. Such an evaluation is essential, as children's speech presents a distinct set of challenge…

Hello, won't you tell me your name?: Investigating Anonymity Abuse in IPFS
Christos Karapapas, Iakovos Pittaras, George C. Polyzos, Constantinos Patsakis
https://arxiv.org/abs/2506.04307

Hello, won't you tell me your name?: Investigating Anonymity Abuse in IPFS
The InterPlanetary File System~(IPFS) offers a decentralized approach to file storage and sharing, promising resilience and efficiency while also realizing the Web3 paradigm. Simultaneously, the offered anonymity raises significant questions about potential misuse. In this study, we explore methods that malicious actors can exploit IPFS to upload and disseminate harmful content while remaining anonymous. We evaluate the role of pinning services and public gateways, identifying their capabilitie…

The billions and billions of dollars this bill pumps into ICE far exceed any conceivable legitimate need the agency could have, even if you agree with its mission.
This bill takes the same masked, anonymous gunmen who have been kidnapping people off the streets and gives them a budget the size of a military.
This is not about honoring the law. This is not even about immigrants.
This is about creating a police state.
I see no other way to read these numbers.
https://mastodon.world/@MJmusicinears/114764606160963355

Tja.
https://newsie.social/@altpapier/114737479765334799

Children's Voice Privacy: First Steps And Emerging Challenges
Ajinkya Kulkarni, Francisco Teixeira, Enno Hermann, Thomas Rolland, Isabel Trancoso, Mathew Magimai Doss
https://arxiv.org/abs/2506.00100

Children's Voice Privacy: First Steps And Emerging Challenges
Children are one of the most under-represented groups in speech technologies, as well as one of the most vulnerable in terms of privacy. Despite this, anonymization techniques targeting this population have received little attention. In this study, we seek to bridge this gap, and establish a baseline for the use of voice anonymization techniques designed for adult speech when applied to children's voices. Such an evaluation is essential, as children's speech presents a distinct set of challenge…