Privacy

The new satellites for missile warning, tracking and targeting are being developed under an “accelerated” schedule to meet the Pentagon’s 2028 plans for demonstrating its Golden Dome missile defense shield.

This year the state of New York had the dubious honor of being the first to pass a controversial provision to mandate all 3D printers come with surveillance and censorship. That means not only is there a ticking clock to protect every artist, researcher, engineer, and hobbyist in the state, but there is a real risk of other states thoughtlessly following suit—prior to the New York rules even taking effect. We, along with many other experts , already warned about this bill buried in the state’s c

The 36 missile warning and tracking satellites are expected to launch by the end of 2028 in support of Golden Dome. The post SDA awards $1.75B in deals for additional Golden Dome missile tracking sats appeared first on DefenseScoop .

Images, videos and voice searches can be used to train Google's LLMs. You can disable this feature to retain your privacy.

Recommender-system research for Vietnamese remains limited by the absence of a public, well-documented hotel interaction resource. Building such a resource is challenging for three reasons: cross-platform hotel names must be reconciled before interactions are comparable; quality must be audited with reproducible metrics rather than ad hoc cleaning; and public release must preserve privacy while remaining benchmarkable under realistic cold-start conditions. We introduce ViHoRec, a quality-control

Publication date: September 2026 Source: Government Information Quarterly, Volume 43, Issue 3 Author(s): Oliver George Kayas, Efpraxia D. Zamani

Publication date: September 2026 Source: Telecommunications Policy, Volume 50, Issue 8 Author(s): Yu-li Liu, Rubing Li, Jiayi Mi, Jiayue Dai, Bo Hu

Publication date: August 2026 Source: Technology in Society, Volume 87 Author(s): Alexandros Apostolakis, Oleg Badunenko, Shabbar Jaffry, Akbar Nasir Khan

Publication date: September 2026 Source: Telecommunications Policy, Volume 50, Issue 8 Author(s): Veronika Horielova, Olena Derevianko, Oleksii Yanushevskyi, Maksym Lysak

Publication date: 2008 Source: Computer Law & Security Report, Volume 24, Issue 6 Author(s): Jari Råman

Publication date: 2008 Source: Computer Law & Security Report, Volume 24, Issue 6 Author(s): Patrick F. Riley

Publication date: November 2026 Source: Computers in Human Behavior, Volume 184 Author(s): Khanh Duy Phan, Bao Quoc Truong-Dinh

Publication date: 2008 Source: Computer Law & Security Report, Volume 24, Issue 6 Author(s): Michael D. Birnhack

Publication date: 2008 Source: Computer Law & Security Report, Volume 24, Issue 6 Author(s): Mark Turner, Tim Gunn

Publication date: 2008 Source: Computer Law & Security Report, Volume 24, Issue 6 Author(s): Harry Small, Helen Kemmitt, Julie Wood, Ben Smith, Nick Wloch

Publication date: 2008 Source: Computer Law & Security Report, Volume 24, Issue 6 Author(s): Roger Baker

Publication date: 2008 Source: Computer Law & Security Report, Volume 24, Issue 5 Author(s): Kate Brimsted

Publication date: 2008 Source: Computer Law & Security Report, Volume 24, Issue 5 Author(s): Mark Turner, Tim Gunn

Publication date: 2008 Source: Computer Law & Security Report, Volume 24, Issue 5 Author(s): Harry Small, Michael Dizon, Rachael Jolley, Matthew Hope, Katie Cullinan

Publication date: December 2026 Source: Computers and Education: Artificial Intelligence, Volume 11 Author(s): William Villegas-Ch, Alexandra Maldonado Navarro, Jaime Govea, Joselin Garcia-Ortiz, Diego Buenaño-Fernandez

Publication date: June 2026 Source: Computers and Education: Artificial Intelligence, Volume 10 Author(s): Lucas Kohnke, Di Zou, Chun Lai, Mingyue Michelle Gu

Societal & User-Centered Privacy in AI (SUPA) Workshop [Seattle, WA, USA] [Aug 10, 2025 - Aug 10, 2025]

This is a current list of where and when I am scheduled to speak: I’m speaking (virtually) at the Policy-Relevant Privacy Research Workshop in Calgary, Canada, on Monday, July 20, 2026. I’m speaking at Boston Leadership Exchange in Boston, Massachusetts, USA, on Wednesday, July 22, 2026. I’m speaking at Cognitive Security Conference in Las Vegas, Nevada, USA. The conference runs August 6-7, 2026; my speaking time is TBD. I’m speaking at DEF CON 34 in Las Vegas, Nevada, USA. The conventions runs

Falling detection is vital for elderly care and intelligent surveillance; however, prevailing vision-based approaches predominantly frame it as static pose classification or discrete temporal pattern matching, fundamentally overlooking the instability dynamics of the human support system. This paper proposes a physics-informed falling detection framework that recasts falling as a stability-loss event in a coupled dynamical system. We introduce a novel dual-LTC architecture comprising a Center-of

This study introduces a unified control framework for fixed-wing unmanned aerial vehicles (UAVs) fitted with a pan-tilt (PT) camera, intended to perform an end-to-end mission spanning from initial target detection to accurate terminal engagement. The proposed system employs a three-phase strategy: a vision-based target acquisition phase, an NMPC-based tracking phase, and a terminal guidance phase. During tracking, the framework uses an Unscented Kalman Filter (UKF) to fuse YOLO-based visual dete

YouTube works well with default settings, but I tighten some privacy controls and enable a few features to make it even better.

In this paper, we challenge the prevailing view that information dependency (including rote memorization) drives training data exposure to image reconstruction attacks. We show that extensive exposure can persist without rote memorization and is instead caused by a tunable connection to adversarial robustness. We begin by presenting three surprising results: (1) recent defenses that inhibit reconstruction by Model Inversion Attacks (MIAs), which evaluate leakage under an idealized attacker, do n

Efforts to bring AI glasses to a broader demographic via a partnership with Kylie Jenner appear to have backfired

arXiv:2607.11127v1 Announce Type: cross Abstract: Organizations and regulators increasingly consult large language models (LLMs) for regulatory-compliance questions, yet a wrong statutory citation can silently propagate into legal advice, compliance documentation, and policy decisions. We introduce a bilingual benchmark of 120 questions probing whether freely accessible LLMs fabricate article citations for two data-protection instruments: the EU General Data Protection Regulation (GDPR) and the

As a pivotal technique in smart healthcare, medical image fusion integrates complementary functional and structural information to facilitate accurate diagnosis and enhance clinical decision-making reliability. However, existing centralized methods typically raise serious data privacy concerns, while standard distributed approaches often fail to balance global generalization with local node personalization due to data heterogeneity. To address this, we propose FLMMIF, a privacy-preserving framew

The Los Angeles police department did not renew its contract with Flock due to data privacy concerns.

Thermal infrared (TIR) imaging is essential for UAV swarm operations in visually degraded environments. However, tracking tiny UAVs remains challenging due to limited appearance cues, frequent occlusions, and rapid maneuvers. Despite significant progress driven by benchmarks such as the Anti-UAV challenge, existing methods primarily prioritize accuracy while overlooking the computational constraints of real-time edge deployment. The standard Kalman Filter (KF) offers the efficiency required for

EPIC submitted testimony on Monday to the D.C. Council Committee on Public Works & Operations urging them to further strengthen B26-0670, the DC Government Data Privacy and Protection Act of 2026.

Large Language Models (LLMs) can make exploratory search more efficient but may undermine the reflection and iterative sensemaking needed in unfamiliar domains. Existing LLM tools often prioritize rapid answers over supporting users in tracking how their understanding evolves and how well their strategies align with their goals. We present TrailLM, a system that helps users reconstruct and revisit their exploration paths to support reflection and metacognitive engagement during information seeki

Large Language Models (LLMs) are rapidly moving from research settings into the wild, deployed on enterprise infrastructure, personal devices, and edge platforms. While cloud deployments offer scalable compute, concerns over data sovereignty, compliance, latency, and third-party dependence are driving organizations toward edge and on-premise LLMs. This shift introduces new security and privacy challenges: limited compute and memory force aggressive optimizations, including quantization, pruning,

WhatsApp usernames may reduce phone number exposure, but in India, they also raise a deeper question...

This article was originally published by IAPP linked here. Organizations using scraped data for AI training should prepare for heightened expectations around data minimization, transparency and accountability. On 7 July, the European Data Protection Board approved “Guidelines on web scraping in the context of generative AI.” Perhaps not surprisingly, the EDPB considers that web scraping [...] The post Thought for the week: Web scraping for generative AI is subject to the GDPR appeared first on C

A public resource tracking all the legal challenges to the Trump administration's executive orders and actions. The post Litigation Tracker: Legal Challenges to Trump Administration Actions appeared first on Just Security .

The China Internet Association released a self-regulatory pact on personal information protection for AI agents at a forum in Beijing, with Baidu, Tencent, Alibaba, Volcengine, and 27 other internet companies among the first signatories. The pact is aimed at standardizing how AI agents collect, process, and use personal data as agent-based services spread across internet […]