Privacy

Protesters allege Mumbai Police used surveillance, detentions and GPS tracking to discourage participation in demonstrations. The post How Mumbai Police is using surveillance to stop youth from protesting appeared first on MEDIANAMA .

Stabile Videos, smartes Tracking und integriertes Licht: Der DJI Osmo Mobile 8 ist bei Amazon zum neuen Bestpreis zu haben. ( Smartphone , DJI )

A U.S. federal case involving GrapheneOS's duress password feature could redefine digital privacy and border phone search laws. The post U.S. man prosecuted over alleged use of phone’s Duress password at border appeared first on MEDIANAMA .

arXiv:2509.10517v3 Announce Type: replace-cross Abstract: Machine learning can predict in-hospital mortality, but data privacy and the statistical heterogeneity of clinical data hamper its use. Federated Learning (FL) is privacy-preserving, yet its behavior under non-IID and imbalanced conditions needs scrutiny. We benchmark five FL strategies - FedAvg, FedProx, FedAdagrad, FedAdam, and FedCluster - for mortality prediction on the MIMIC-IV dataset, partitioning 466,351 admissions across five car

Machine unlearning, which aims to remove the influence of specific training data from a trained model, is a key requirement for privacy, accountability, and adaptive deployment. We argue that many unlearning methods are vulnerable to a simple clustering attack, which can recover class structure in an unsupervised manner, limiting their suitability for continual deployment where removal requests must be handled reliably on demand. To address this, we propose DECAF (DE-Clustering for Adaptive Forg

Face recognition systems are widely used in surveillance, biometric authentication, access control, and digital identity verification; however, supervision sensitivity, evaluation stability, and performance consistency across datasets remain insufficiently understood. This study investigates the behavior of convolutional, transformer-based, and hybrid face recognition architectures under both Softmax and ArcFace supervision using five-fold subject-disjoint cross-validation on the Labeled Faces i

Biomedical image analysis spans diverse modalities and tasks, yet real-world deployment is hindered by severe distribution shifts across scanners, protocols, and patient populations. High-performing models consequently require repeated domain-specific fine-tuning, which is a costly cycle that becomes impractical when labels are scarce or privacy constraints limit data sharing. We propose OPERA (Offline Policy-guided Expert Routing and Adaptation), a multi-agent ensemble framework that addresses

The Apple team behind the upcoming smart glasses is reportedly exploring several tweaks related to user privacy.

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Differential privacy provides formal privacy guarantees for training neural networks on sensitive data, while Bayesian deep learning offers a principled framework for uncertainty-aware prediction. Combining these two objectives remains challenging, as privacy noise can interact with the stochasticity introduced by Bayesian posterior sampling. In this work, we investigate differentially private variational Bayesian learning through the Improved Variational Online Newton (IVON) optimizer. We intro

As a writer who covers baby and kids gear, I'm inundated with emails about the hottest new toys: a box that automatically prints pictures based on kids' commands. A robot with facial recognition capabilities. A teddy bear that can craft end ... (https://incidentdatabase.ai/cite/1277#7589)

Democrats, Republicans and political consultants fear New Jersey’s new law could slap their campaigns with hefty fines.

Lawsuit Challenges Secret Government Policy that Collects, Stores, and Uses Personal Information About People Observing Immigration Enforcement SAN DIEGO — Privacy rights advocates and three individuals today filed a lawsuit challenging the Trump-Vance administration’s unlawful surveillance of those who peacefully observe and document federal immigration enforcement. Plaintiffs allege that the U.S. Department of Homeland Security (DHS) has … Continued

Lawsuit Challenges Secret Government Policy that Collects, Stores, and Uses Personal Information About People Observing Immigration Enforcement SAN DIEGO — Privacy rights advocates and three individuals today filed a lawsuit challenging the Trump-Vance administration’s unlawful surveillance of those who peacefully observe and document federal immigration enforcement. Plaintiffs allege that the U.S. Department of Homeland Security (DHS) has … Continued

Geometry Foundation Models (GFMs) have substantially advanced monocular 3D reconstruction, yet extending this capability to 4D dynamic understanding remains a fundamental challenge. Most existing motion perception methods (e.g., sparse tracking, dense point-wise flow) treat motion as independent point-wise displacements, ignoring the structured nature of physical motion. However, real-world objects usually obey rigid-body kinematics, and points thus usually move collectively, not in isolation. M

The European Commission on Friday said it found TikTok had not adequately protected children’s privacy rights on its platform by allowing adults to view the accounts of minors. The action exposed children to cyberbullying, unwanted contact and predatory behavior, commission spokesperson Thomas Regnier said. “Children’s content must never be visible to strangers,” he said. If TikTok does not take steps called for by the European Union’s landmark Digital Services Act , “minors are exposed to preda

Register now for MediaNama's online briefing on July 28, 2026, exploring internet shutdowns, BitChat, facial recognition, and protest surveillance. The post Briefing Call Announcement: Tech and the Cockroach Janata Party Protests, July 28, 2026 #NAMA appeared first on MEDIANAMA .

Reporters at Jantar Mantar protests allege that Delhi Police has deployed vans with CCTV cameras at both ends, capturing protesters and identifying them using facial recognition technology. The post Delhi police use CCTV surveillance for live facial recognition at Jantar Mantar protests appeared first on MEDIANAMA .

Some institutions are overhauling assessment and trying to move away from the emphasis on surveillance

In the past decade, we have witnessed an exponential growth of deep learning models, platforms, and applications. While existing DL applications and Machine Learning as a service (MLaaS) frameworks assume fully trusted models, the need for privacy-preserving DNN evaluation arises. In a secure multi-party computation scenario, both the model and the data are considered proprietary, i.e., the model owner does not want to reveal the highly valuable DL model to the user, while the user does not wish

The South African Social Security Agency (SASSA)'s biometric verification drive has intensified efforts to clamp down on fraud in the social grant system, after Parliament was told that nearly one million beneficiaries have been processed s ... (https://incidentdatabase.ai/cite/1606#7574)

Privacy-preserving machine learning auditing protocols allow auditors to assess models for properties such as accuracy or fairness, without revealing their internals or training data. This makes them especially attractive for auditing models deployed in sensitive domains such as healthcare or finance. For these protocols to be meaningful in real-world audit settings, though, their guarantees must reflect how the model will behave once deployed, rather than merely certifying its behavior during a

Police departments across the country are lining up to launch drone-as-first-responder (DFR) programs, and hundreds have cleared a necessary hurdle toward making deployment a reality, expanding aerial surveillance and data collection even in areas patrol officers typically can't reach. As of February 2026, over 1,000 public safety agencies —including police, fire, and other emergency management agencies—had received Federal Aviation Administration (FAA) waivers needed to automate drone operation

Teachers, conference chairs, and public readers all judge writing from limited evidence, seeing only a finished document and not the process that produced it. Final text alone cannot reveal whether a document was produced through human typing, AI generation, or mixed human-AI collaboration. Existing process-tracking tools help, but many are tied to host-document histories, provide coarse activity records, and offer limited control over the writing environment. Humanly is a writing platform that

A consensus anomaly detection framework was applied to monthly malaria surveillance data from Ghana (2014-2023) to identify atypical transmission patterns. Anomalies were highly structured in space and time. Ashanti and Northern Regions accounted for most recurrent anomalies, with persistent hotspots at Tamale, Kumasi, and Accra. A key finding was the spatial distinction between anomaly burden (cumulative cases during anomalous periods) and anomaly frequency (persistence of unusual behaviour). T

OpenAI is rolling out ChatGPT Health to everyone in the US on Thursday, allowing more people to connect their medical records and health-tracking information to the chatbot. During a briefing, Ashley Alexander, OpenAI's vice president of health product, says the company's models "are now capable of reasoning at levels that are better than clinician level." […]

Michael Hanna-Butros Meyering, Nevada's chief communications and policy officer, will now help Oregon translate privacy principles into practical decisions and repeatable processes, according to a state announcement.

Integrating heterogeneous biomedical data, including clinical metadata, histopathology images, and molecular profiles, is crucial for comprehensive disease understanding. However, gene expression data acquisition remains constrained by high costs and privacy concerns, limiting its use in multimodal research and AI-driven applications. We present MultiModal Molecular Generation (M$^3$-Gen), a novel framework for the generation of gene expression profiles by conditioning a Generative Adversarial N

It can be unsettling what Gemini and ChatGPT have figured out about you and how easily your privacy can be punctured. Here’s how to find out.

On Thursday, New Jersey Governor Mikie Sherrill signed into law a ban on surveillance pricing for groceries. The Fair Price Protection Act makes New Jersey the third state to enact legislation curbing surveillance pricing, joining Maryland and Connecticut. The New York Legislature has also sent a surveillance pricing ban to Governor Kathy Hochul’s desk for signature.

This past school year, Cambridge, Massachusetts, placed every eighth grader in Algebra I. It didn’t go well. Ultimately, more than 60% of rising ninth graders will repeat the course.  The consequences were immediate: weeping students, angry parents, and roiling debate about the rollout, teacher support, and tracking. Lost in the shuffle was this essential point: We teach obsolete rote math that adults don’t use, while missing entirely the math that defines our lives.   Let’s start

US scrutiny of Chinese technology has expanded to a new frontier, as lawmakers in Washington advance defence legislation prohibiting the military from deploying Chinese-made humanoid robots. The US House of Representatives has passed the National Defence Authorisation Act (NDAA), an annual military policy bill that incorporates provisions restricting the use of foreign autonomous systems over national security and data privacy concerns. Under Section 163 of the draft bill, the Pentagon would be.

Brussels has developed a curious theory of digital privacy. Anonymous search queries need audits, screening, and a security cordon. Your messages, microphone, and screen can make do with a checkbox. That is the logic running through two decisions the European Commission adopted last week involving the same company, under the same law, on the same ... Europe’s Privacy Paradox: Fort Knox for Search Data, a Checkbox for Your Phone The post Europe’s Privacy Paradox: Fort Knox for Search Data, a Chec

Today's links California's privacy obstacle course: Malice or incompetence (why not both?). Hey look at this: Delights to delectate. Object permanence: Continuous partial attention, TSA is the worst; Trump's FCC v the future. Upcoming appearances: Edinburgh, Sydney, Melbourne, Brighton, London, South Bend. Recent appearances: Where I've been. Latest books: You keep readin' em, I'll keep writin' 'em. Upcoming books: Like I said, I'll keep writin' 'em. Colophon: All the rest. California's privacy

Preprocessing blood glucose time-series data is a critical yet often overlooked step in developing data-driven methods for diabetes management, particularly for type 1 diabetes. The lack of standardized preprocessing workflows and evaluation protocols hinders reproducibility and complicates fair comparison across studies. These challenges are further exacerbated by data-sharing restrictions, as privacy and licensing constraints often prevent the redistribution of preprocessed medical datasets. T

Deep subspace clustering plays a critical role in applications involving multivariate spatiotemporal data, such as sea ice monitoring, disease spread analysis, and tracking neuro-degeneration over time. Despite recent advances, existing methods primarily rely on geometric self-expressiveness, assume static subspace structures, and often fail to capture causal dependencies, local spatial interactions, and long-range temporal dynamics inherent in complex spatiotemporal systems. To address these li

Traditional approaches to wearable health signal analysis, such as smartwatches, are constrained by rigid analytical frameworks and limited personalisation. The emergence of LLM agents creates a new opportunity for Personal Health Agentic Analysis, where health insights can be generated adaptively and in context. However, currently there is no open-source locally deployable platform capable of processing personal health data in real time while preserving privacy. We present HiMe, a locally deplo

arXiv:2607.19403v1 Announce Type: cross Abstract: Validating federated learning frameworks on real clinical data is an essential step between proof-of-concept demonstrations in controlled synthetic environments and deployment in real multicenter healthcare settings. A prior architectural study by the same authors (Tertulino and Alencar, 2026) demonstrated, on a synthetic six-feature benchmark, that server-side adaptive optimization acts as a temporal denoiser for Differential Privacy noise, answ