Privacy

arXiv:2607.19949v1 Announce Type: cross Abstract: Smartphone personal assistants reason over longitudinal personal data, yet evaluating them requires context-rich evaluation data whose correct answers are known, and real device traces are too privacy-sensitive to share. To address this challenge, we present SenWorld, a physically grounded, deterministic, event-sourced digital-twin simulation that generates such data with ground truth fixed by construction. In SenWorld, personas live through a fu

IntroductionImages from crime scenes often show partially concealed weapons due to obstructions such as hands and clothing, as well as surveillance camera limitations, which affect the efficacy of traditional detection methods. This work proposes an explainable forensic pipeline for occluded weapons detection, segmentation, and reconstruction.MethodsThe proposed framework integrates RT-DETR-L, a transformer-based weapon detection model; MobileSAM for zero-shot segmentation of visible weapon regi

The growing need for secure and convenient authentication methods has led to the increasing popularity of biometric solutions. In addition to traditional and popular methods, such as fingerprint or iris scanning, voice-based approaches are also employed. User identity verification based on voice is conducted using Automatic Speaker Verification (ASV) systems. Despite their many advantages, these systems are sensitive to various types of attacks and acoustic noises, which can reduce verification

A malicious application delivers four-stage Android spyware via phony Google Play sites, exploiting civilian fear during Iranian missile strikes.

Clinical biomarker workflows in translational research settings often rely on spreadsheet-driven tracking, manual quality control (QC) reconciliation, and loosely integrated systems, resulting in limited state visibility, delayed reporting, and increased operational risk. These challenges are particularly pronounced in multi-day assays such as Luminex-based quantification of Fragile X Messenger Ribonucleoprotein (FMRP), where HIPAA-compliant data governance, deterministic workflow progression, a

Containers are a boon to your browsing security and privacy. Out of the box, Firefox now gives you four pre-configured containers: Personal, Work, Banking, and Shopping.

RGB-D semantic segmentation has achieved remarkable progress, yet most models assume that RGB and depth are always available. In practice, failures or occlusions of surveillance sensors often remove one modality. Although RGB or depth alone can contain sufficient cues, models trained only on full-modality inputs fail to exploit the remaining modality once one is missing, causing severe degradation. We tackle this issue with a simple continued-training paradigm, \emph{Condition Dropout (ConD)}, w

The use of LLMs for foreign intelligence surveillance erodes the rules put in place to safeguard Americans' civil liberties. The post AI and Warrantless Foreign Intelligence Surveillance appeared first on Just Security .

Jake Mannix discusses moving AI agents past chaotic "1970s BASIC" architectures. He shares how implementing an intermediate protocol layer allows engineering leaders to build versioned, encapsulated "virtual tools." This design enables interface mapping, dynamic schema projection, and runtime taint tracking to proactively eliminate data exfiltration risks without slowing velocity. By Jake Mannix

What GAO Found The Individual Longitudinal Exposure Record (ILER) is a web application that links service members’ and veterans’ military toxic exposures and related information from Department of Defense (DOD) and Department of Veterans Affairs (VA) databases. DOD and VA intend ILER to be a multi-purpose tool to support clinicians in providing diagnoses and treatment decisions, researchers in conducting health surveillance and epidemiological research, and Veterans Benefit Administration (VBA)

European and US banks inadvertently transmitted customer data to ad platforms via tracking pixels, raising serious compliance, security, and privacy concerns.

Academic Freedom at UT ‘Being Dismantled,’ Says Professor Denied Tenure Emma Whitford Wed, 07/22/2026 - 03:00 AM Border-surveillance researcher Iván Chaar López received a near-unanimous recommendation from faculty and outstanding external support letters. Still, he was denied tenure without explanation. Byline(s) Emma Whitford

Meta has introduced parental supervision tools for Threads, allowing parents to track teen usage, set time limits, and manage privacy settings. The post Meta adds parental controls to Threads nearly three years after launch appeared first on MEDIANAMA .

Critics may label the initiative as 'Privacy sandbox 2.0,' but advocates counter with privacy arguments.

arXiv:2607.18424v1 Announce Type: new Abstract: Automated analyses of privacy policies enable large-scale assessments of transparency in digital ecosystems, yet existing auditing pipelines remain predominantly English-centric. This limits their ability to systematically evaluate multilingual environments, as in the European Union, where many services disclose privacy practices only in local languages. This paper examines whether large language models (LLMs) can extend privacy policy analysis bey

Quantum federated learning enables distributed clients to train quantum neural networks without sharing local data, making it promising for privacy-aware intelligent services. Intelligent services in this context refer to privacy-sensitive distributed decision systems, such as fraud detection and genomic classification, where reliable and fair client-level learning is as important as the accuracy of the aggregate model. However, heterogeneous client data and noisy quantum optimization often caus

Federated Learning (FL) enables collaborative model training without centralizing raw data, but building and operating FL systems remains difficult due to distributed execution, rapidly evolving frameworks, and privacy and governance requirements. In this paper, we present an empirical study of FL developer challenges by independently analyzing 495 Stack Overflow posts and 9,116 GitHub issues and pull requests from 92 FL-related projects. Using BERTopic-based topic modeling and difficulty indica

Data-privacy experts said on a recent panel that while state privacy laws regulate what data brokers can collect and sell, those laws often do not extend to the problematic conclusions those companies can infer.

Differentially private machine learning enables model training on sensitive data while ensuring that individual data is unlikely to be recoverable from the parameters of the resulting model. However, existing work often privatizes both training inputs and their labels, and these protections may be conservative when labels are public or can be safely made public. Therefore, in this work we propose a novel private training framework that instead privatizes training inputs while keeping labels publ

Embodied visual tracking (EVT) requires a mobile agent to continuously follow a specific target described in natural language using only onboard vision. While recent vision-language-action (VLA) policies unify target identification and trajectory planning, their chain-of-thought (CoT) reasoning often operates in abstract spatial latents that are difficult to supervise and weakly aligned with explicit image-space detections. To address this, we introduce ReferTrack, a referring-then-tracking para

Washington, D.C. — Today, EPIC and the National Institute for Workers' Rights (NIWR) released a white paper titled Who's Got the Power? Restoring Worker Power in the Age of Algorithmic Unionbusting, documenting how employers increasingly use surveillance technologies, algorithmic management systems, and vast stores of worker data to identify, monitor, and interfere with workers seeking to organize.

Federated learning has emerged as a potential solution to privacy concerns associated with using sensitive health data for training predictive models, particularly in personalised cancer care. This research investigates whether federated learning can support the development of robust models for predicting tumour progression in breast cancer patients while addressing four critical deployment pillars: transparency, scalability, security, and fairness. This study evaluates a federated learning fram

As pathogen genomic surveillance scales, the bottleneck is shifting from data generation to analysis. We present BioSecBench-Surveillance, a verifiable benchmark of 100 evaluations testing whether AI agents can infer the right analysis pipeline from raw sequencing data and surveillance context. Each evaluation gives an agent only the data and context a human analyst would have, then grades its structured answer deterministically. The tasks span seven categories, from taxonomic classification to

Continual learning (CL) has been recently employed in biometric identification systems thanks to its ability to integrate new knowledge within a pre-trained model and to the possibility of reducing the computational cost of training. Unfortunately, such approaches pose new challenges both in terms of final accuracy and privacy guarantees since a progressive fine-tuning of the model on small subsets expose them to catastrophic forgetting and successful inference attacks. This paper evaluates the

Washington, D.C. — Today, EPIC and the National Institute for Workers' Rights (NIWR) released a white paper titled Who's Got the Power? Restoring Worker Power in the Age of Algorithmic Unionbusting, documenting how employers increasingly use surveillance technologies, algorithmic management systems, and vast stores of worker data to identify, monitor, and interfere with workers seeking to organize.

The Pentagon’s new deals to deploy commercial LLMs on its classified networks provide it with a powerful surveillance capability that could be turned on Americans. The post AI and the Commercial Data Loophole appeared first on Just Security .

Personal AI is moving beyond chat-only interaction toward continuous services that span phones, cars, homes, wearables, cameras, and tools. In this setting, memory cannot remain a cache of prior conversations. It should serve as a continuity and governance substrate: preserving durable user state, grounding answers in multimodal and device evidence, supporting correction and forgetting, bounding policy evolution, and remaining deployable under latency, cost, privacy, and edge-cloud constraints.

It’s a lot : According to information obtained by The Tech , MIT is spending over $3 million on more than 500 AI surveillance cameras in academic buildings, residence halls, and outdoor areas along Memorial Drive. Installation of the new cameras, along with the wiring and infrastructure that will support them, began November 2025 and will likely continue until September 2026. Technical specifications for the cameras suggest that they will be capable of collecting real-time face and object classi

Le « Q-Day » pourrait avoir lieu aux alentours de 2030-2035, même si actuellement les machines quantiques rencontrent de nombreuses limitations. Les pays et les services de renseignements se préparent car la guerre fait déjà rage sur les financements, les brevets et les ingérences avec des laboratoires de recherche sous surveillance. La Cour des comptes […]

Terming the PIL alleging Delhi Police surveillance on Jantar Mantar protesters as "luxury litigation", the Solicitor General said, "every protest is always recorded" & it's only for "law and order" purpose not snooping. The post Delhi Police says Jantar Mantar protest videography is for law and order, not surveillance appeared first on MEDIANAMA .

Wearable photoplethysmography (PPG) provides continuous heart-rate measurements, but its accuracy degrades under motion. In the ring-platform benchmark, the best supervised baseline reaches 5.33 BPM mean absolute error (MAE) on the overall heart-rate task. In the motion-focused ring-only audit, a supervised LSTM baseline reaches $14.39 \pm 0.47$ BPM MAE on motion windows, and simple smoothing and ACC priors reduce this only to $13.00 \pm 0.41$ BPM. This thesis addresses motion-corrupted HR estim

Border Surveillance Scholar Denied Tenure at UT Austin Emma Whitford Tue, 07/21/2026 - 03:00 AM Byline(s) Emma Whitford

The proposal aims to provide a browser-based mechanism for measuring advertising performance without relying on cross-site tracking.

arXiv:2607.16223v1 Announce Type: new Abstract: The rapid integration of generative artificial intelligence (AI) has reshaped the landscape of higher education. Students have embraced tools such as ChatGPT with striking speed, while teaching staff and institutions have responded with greater caution. Existing research on AI perceptions has mainly been cross-sectional, providing single-point snapshots that view attitudes as stable rather than evolving. This paper presents a longitudinal study of

arXiv:2607.16513v1 Announce Type: new Abstract: AI-driven algorithms and automated tools are increasingly embedded in the correctional landscape, shaping parole eligibility,release decisions, and surveillance. These tools are also often framed as objective, inevitable solutions to inefficiency andbias. Yet, these computational systems are rarely designed with input from justice-impacted individuals, which means theymight fail to address the real needs of incarcerated people. To address this gap,

arXiv:2607.16620v1 Announce Type: cross Abstract: Differential privacy (DP) is increasingly deployed to limit membership inference risk in machine-learning systems. Prior work has shown that DP-SGD can widen accuracy disparities across demographic groups, but this framing treats fairness as a purely outcome-side concern. We argue that privacy cost, the information leakage borne by each group, is itself a form of harm, and adopt a compensatory-fairness framework in which a group that involuntaril

arXiv:2506.20463v2 Announce Type: replace-cross Abstract: Generative artificial intelligence (GenAI) is transforming the educational landscape by augmenting learning paradigms. However, state-of-the-art GenAI systems driving this transformation are predominantly developed and controlled by a small number of private companies; there is little clarity about their data retention practices and limited user control over inputs and outputs. In the context of education, end-users lack the awareness of

As hospitals increasingly use AI to improve patient care, the same technology is being used by hackers and nation-states to launch faster, more sophisticated attacks. Karen Habercoss, chief information security and privacy officer at the University of Chicago Medicine, explained how her health system is building a governance structure to manage that risk. The post The Same AI That Helps Patients Is Being Used to Attack Them, Hospital Exec Says appeared first on MedCity News .

Are you a California resident? Then we've got exciting news for you: there's a tool just for you that lets you take a single, relatively easy step to protect your privacy. It's called a DROP request. (That's Delete Request and Opt-out Platform, if you're fancy). This one bit of paperwork lets you tell every data broker registered in the state of California that you'd like them to delete your information from their databases and request they stop selling and sharing your information. Here are som

A new report from the Government Accounting Office reveals that the Department of Homeland Security (DHS) plans to nearly triple the number of surveillance towers along U.S. borders, from the current 830 to 2,300 by 2034. DHS expects to expend $1 billion in taxpayer dollars for this dangerous expansion of a surveillance network indiscriminately trained on towns, school playgrounds, backyards, and vehicles—threatening the privacy and civil liberties of everyone in the border regions. The towers a