Search: “privacy”

Microsoft has new AI privacy rules for schools

Microsoft agreed to enforceable AI safety and privacy principles with the AFT and UFT after New York City and Los Angeles imposed one-year bans on student-facing AI.

Microsoft committed to ten contractually enforceable principles covering AI use in schools, including not training models on student or educator data, limiting data collection, plain-language disclosure to families, prohibiting AI companions, and requiring human review for high-risk decisions. The agreement with the American Federation of Teachers and its NYC affiliate comes after NYC and LA implemented one-year bans on student-facing AI. Districts can adopt the terms into new or existing contracts starting in November.

The Verge · AI·Sep 9, 17:07 UTC · 6d agoAI policy

Private Information Retrieval With Arbitrary Privacy Requirements: Introduction and Capacity Results

Researchers formulate private information retrieval under arbitrary graph-based privacy requirements, deriving capacity bounds and introducing pyramid storage graphs.

The paper generalizes classical private information retrieval (PIR) to arbitrary privacy requirements over graph-based storage systems, where each message is retrieved privately from a pre-specified server subset. The authors derive lower and upper capacity bounds for general graphs and exact capacity results for path and cyclic storage graphs. They also introduce a new pyramid storage graph structure that models symmetric message storage and replication patterns.

arXiv cs.CR·Sep 14, 17:03 UTC · 1d agoResearch

RegionFed: Federated Learning for Personalized Query Understanding in Heterogeneous Retail Environments

RegionFed is a gradient-level federated learning framework enabling personalized retail query understanding while matching centralized accuracy with differential privacy.

RegionFed is an architecture-robust federated learning framework for personalized query understanding that operates at the gradient level, using the l2 conflict between regional and global gradients to diagnose heterogeneity and control personalization. Existing parameter-level personalized FL methods collapse on transformers, falling below 10% accuracy on T5, while RegionFed deploys unchanged on T5-Small, T5-3B, RoBERTa, and CNNs. RegionFed-Meta achieves 92.27% across Amazon ESCI, Amazon Reviews, and LEAF-FEMNIST, within 0.23 percentage points of the centralized upper bound, with epsilon-approx-0.60 differential privacy.

arXiv cs.AI / cs.LG / cs.CL·Sep 4, 17:50 UTC · 11d agoAI research1

Differential Privacy Meets Fixed Parameter Tractability: Algorithms and Lower Bounds

Theory paper combines differential privacy with fixed-parameter tractable encoders, improving approximation guarantees for combinatorial optimization and proving new lower bounds.

The paper studies combinatorial optimization under epsilon-differential privacy within the implicit encoder-decoder framework of Gupta et al. (SODA 2010), generalizing it to allow fixed-parameter tractable encoders. This circumvents approximation barriers inherent to polynomial-time algorithms and yields improved guarantees for fundamental combinatorial optimization problems. The authors establish the first representation-independent lower bounds: assuming a non-uniform variant of the Gap Exponential Time Hypothesis, no epsilon-DP encoder-decoder pair can achieve certain approximation guarantees with a subexponential-time decoder for sufficiently small epsilon. Representation-dependent lower bounds are also provided for larger epsilon.

arXiv cs.CR·Sep 11, 07:13 UTC · 5d agoResearch

Cybersecurity jobs available right now: August 25, 2026

Help Net Security lists open cybersecurity roles at AT&T, Accenture, Mastercard and others across the US, Europe, India and UAE.

Help Net Security aggregated open cybersecurity positions including compliance, IAM engineering, security architecture, SOC analyst and cloud security roles. Employers include AT&T, Accenture, Mastercard, Insight, Mitiga, NEURA Robotics and Abu Dhabi Islamic Bank across the US, India, France, Germany, Ireland, Israel and UAE. Several postings emphasize identity and access management, NIS2 and GDPR compliance, and cloud security work.

Help Net Security·Sep 3, 08:28 UTC · 13d agoIndustry

Understanding the Privacy-Preserving Potential of HTTP/2 Against Webpage Fingerprinting

Researchers show HTTP/2 features can emulate website fingerprinting defenses like FRONT and Tamaraw with tunable privacy-overhead trade-offs.

An arXiv paper demonstrates that application-layer defenses such as HTTPOS, LLaMA, FRONT, ALPaCA, and Tamaraw can be emulated through HTTP/2 features at both the client and server side, including proactive resource suggestion, multiplexing, and flow control. The authors propose a unified evaluation blueprint that calibrates defense parameters per dataset, combines practical attacks with information-theoretic leakage estimators, and measures overheads to map each defense's privacy-overhead trade-offs.

arXiv cs.CR·Sep 4, 13:16 UTC · 11d agoResearch

Notes on gotchas while migrating 35kb preprompts from Opus to self-hosted Ollama

Opinion piece urges migrating 35KB preprompts from Anthropic/OpenAI to self-hosted Ollama, citing session privacy risks and safety filters blocking security research.

The author documents gotchas migrating 35KB preprompts from Claude Opus to self-hosted Ollama, motivated by fears that frontier providers train on user sessions, citing the OpenAI Navier-Stokes controversy. The piece argues inference providers cannot audit their own retention or training pipelines and that only self-hosted hardware offers verifiable privacy. It also criticizes frontier safety filters for refusing vulnerability research tasks and calls for models that support exploitability testing in CI/CD pipelines.

Hacker News · AI·Sep 14, 13:59 UTC · 1d agoAI industryHN 41↑ · 13 comments1

PrivAudit: A Dual-Lens Auditing Framework for Website Privacy Practices under the CCPA

PrivAudit framework audits 998 websites for CCPA compliance, finding stronger disclosures but pervasive, weakly responsive third-party cookie tracking.

PrivAudit is an automated dual-lens auditing framework combining LLM-based analysis of privacy policies grounded in CCPA provisions with automated browser measurements of cookie writes under diverse privacy configurations. Applied to 998 websites, it finds CCPA-subject sites disclose opt-outs, data sharing, and user rights more frequently, yet tracking remains pervasive: 6,392 targeting cookies, 49% third-party writes. Cookies show limited-to-moderate responsiveness to privacy signals and consent choices even when sites claim to honor them. The framework is open-sourced and shared with regulators.

arXiv cs.CR·Sep 9, 04:31 UTC · 7d agoResearch

The SCREEN Act is a Christian Nationalist Nightmare

404 Media·Aug 4, 17:41 UTC · Aug 4, 2026Policy & legal

Predicting Privacy Leakage from Weight Spectral Density

Study shows WeightWatcher spectral metrics like stable rank correlate with membership inference vulnerability, enabling cheaper ML privacy auditing.

The paper tests whether spectral metrics from the heavy-tailed self-regularisation framework can proxy membership inference attack (MIA) vulnerability without training expensive shadow models. On image and tabular classification tasks, stable rank correlates positively with overall MIA success, while Log alpha-Norm correlates negatively at the low false-positive regime. These correlations are stronger than those obtained from the generalisation gap, suggesting weight spectra capture leakage information overfitting measures miss. The authors propose spectral analysis as a scalable direction for privacy auditing.

arXiv cs.CR·Sep 10, 16:34 UTC · 5d agoResearch

Top 10 Best Data Security Posture Management (DSPM) Tools in 2026

A 2026 scorecard ranks DSPM tools with Wiz and Cyera tied first, documenting consolidation via Palo Alto, Rubrik, Proofpoint, and CrowdStrike acquisitions.

The article ranks ten DSPM platforms: Wiz and Cyera tie at 8.7/10, followed by BigID at 8.5 and Securiti at 8.4, scored on discovery breadth, classification accuracy, access context, remediation, and value. It highlights heavy market consolidation, noting Dig Security was acquired by Palo Alto Networks, Laminar by Rubrik, Normalyze by Proofpoint, and Flow Security by CrowdStrike. Buyers are advised to purchase from current owners and confirm post-acquisition integration state.

Cyber Security News·07:29 UTC · 2h agoIndustry

Differentially Private EEG Feature Anonymization: A Privacy-Utility Case Study in Clinical Neurophysiology

Case study applies Gaussian and Laplace differential privacy to clinical EEG features, quantifying privacy-utility trade-offs across three deployment scenarios.

Researchers evaluate subject-level differential privacy for EEG-derived feature representations using Gaussian and Laplace perturbations across client-side, centralized server-side, and decentralized local training scenarios. Utility is assessed with statistical measures and a downstream machine-learning check on clinical neurophysiology data. Results show DP can be integrated into EEG workflows, but mechanism choice, privacy parameters, and sensitivity calibration strongly influence data utility, particularly on small and imbalanced clinical datasets. The study highlights the privacy-utility trade-off in protecting biomedical signals against re-identification and inference risks.

arXiv cs.CR·Sep 10, 16:31 UTC · 5d agoResearch

25 Years of Mass Surveillance Is Enough

Bruce Schneier and Cindy Cohn argue post-9/11 mass surveillance expanded far beyond its counterterrorism justification and should be reevaluated for costs to rights.

An essay by Bruce Schneier and Cindy Cohn (originally in Lawfare) traces the post-9/11 shift from targeted surveillance to mass collection of telephone and internet metadata. It cites the Section 215 bulk phone records program, struck down in interpretation by the Second Circuit in 2015 and curtailed by the USA Freedom Act, and the NSA's Upstream program under Section 702 of the 2008 FISA Amendments Act, which ended content searches in 2017. The authors note mass surveillance now serves routine law enforcement and immigration actions, with FBI Director Kash Patel confirming purchases of Americans' data from brokers, and private systems like Flock license plate readers and venue facial recognition feeding government access.

Schneier on Security·Sep 15, 11:01 UTC · 23h agoPolicy & legal

Stopping the smart TV from being used against you

Guide describes practical hardening steps to prevent smart TVs from spying on their owners or being used against them.

A tutorial-style post walks through defensive measures to keep a smart TV from collecting user data or being leveraged against its owner. The piece is a consumer IoT privacy and hardening guide rather than a disclosure of a specific vulnerability.

Lobsters · security·Aug 28, 19:32 UTC · 18d agoResearch

Topological Fraud Detection in Latent Transaction Spaces

Researchers present a privacy-preserving fraud detection method combining unsupervised filtering and supervised classification on anonymized transaction embeddings for low-latency triage.

The paper describes fraud detection performed entirely on topologically anonymized transaction embeddings. It iterates unsupervised filtering followed by supervised classification ('sniping') to flag suspicious activity. The goal is ultra-low-latency, privacy-preserving triage for institutions without exposing personally identifiable information.

arXiv cs.CR·Sep 8, 08:50 UTC · 8d agoResearch

Machine Unlearning as Private Retroactive Algorithms

A cs.CR paper defines private retroactive algorithms, showing machine unlearning is a data-maintenance problem and giving DP constructions for linear statistics, clustering, histograms.

The paper argues that machine unlearning's requirement to emulate retraining from scratch carries no meaningful privacy semantics against adversaries observing sequences of releases, recasting it as a data-maintenance question addressed by retroactive algorithms. It defines private retroactive algorithms, combining retroactivity with differential privacy under continual observation. Constructions achieve privacy and retroactivity at no asymptotic cost over privacy alone for linear statistics, clustering, and histograms, alongside impossibility results.

arXiv cs.CR·Sep 4, 16:32 UTC · 11d agoResearch

Cybersecurity jobs available right now: March 10, 2026

Help Net Security's roundup lists open cybersecurity roles at BioNTech, AIG, ServiceNow and others across Europe, the Middle East and Canada.

A job-board roundup of cybersecurity openings including Associate Director Application Security at BioNTech (Germany), CISO at AIG (Israel), Cloud Security Professional at ServiceNow (Italy), and SOC/GRC, analyst, engineer and data governance roles in the UK, UAE, India, Canada and France. Roles span application security, cloud security, SOC operations, compliance and OT environments. Most listings are marked no longer accepting applications.

Help Net Security·Aug 28, 09:06 UTC · 19d agoIndustry

Some Claude Chats Are Searchable on Google

Schneier on Security·Aug 4, 10:13 UTC · Aug 4, 2026Data breach2

Kids’ online safety bill faces dim prospects of passage this session despite progress

Kids Online Safety Act clears Senate committee but passage looks unlikely this session amid House-Senate deadlock over the duty-of-care provision.

KOSA advanced out of the Senate Commerce Committee, but the chambers remain split on a duty-of-care provision requiring platforms to act with reasonable caution to prevent foreseeable harm, which House leadership opposes over First Amendment and negligence-lawsuit concerns. The Senate passed KOSA 91-3 last Congress before it died in the House, and the House passed its own version without the duty of care in June as part of a larger package, after stripping a state-law preemption provision. Observers say even Senate passage this year is a struggle given the short calendar, with a lame-duck window between November and January the more plausible path, and Majority Leader John Thune controlling whether a roll-call vote happens.

The Record·Aug 24, 00:00 UTC · 23d agoPolicy & legal

Why User Studies and Participant Experience Reporting Matter for VR Motion Privacy?

User studies explain VR motion privacy mechanism acceptance far better than physical deviation metrics, a study of three mechanisms finds.

The paper examines how well physical deviation predicts user acceptance of VR motion privacy mechanisms compared to user studies, testing three mechanisms at five deviation levels. User studies explain substantially more variation in mechanism acceptance, though physical deviation remains significant, and prior VR experience affects acceptance. Public VR game leaderboards expose motion recordings from hundreds of thousands of users, creating identification and profiling risks. The authors recommend combining physical deviation metrics with user studies and reporting participants' prior experience.

arXiv cs.CR·Sep 11, 04:08 UTC · 5d agoResearch

FBI officials say AI is bolstering adversaries, emphasizing need to focus on cyber basics, patching

FBI officials said AI is accelerating adversary capabilities while its new cyber strategy emphasizes continuous patching, cyber hygiene, and AI-enabled defense.

At the Billington CyberSecurity Summit and ahead of a new FBI cyber strategy, deputy assistant director Jason Bilnoski said AI is boosting the speed and capability of both criminal and nation-state attackers, while stressing that basic controls like MFA would still prevent most attacks. Colleen Ferranti urged a shift from quarterly Patch Tuesday cycles to continuous, risk-based patching as AI accelerates vulnerability discovery. The strategy pledges AI-enabled triage, malware analysis, attribution support, agentic AI adoption, expanded Computer Network Operations, ICS Coordinators in every field office, and a pledge on victim relief and privacy.

CyberScoop·Sep 9, 13:00 UTC · 6d agoPolicy & legal

PIA-Bench: Towards Automated Privacy Impact Assessment with Large Language Models

Researchers release PIA-Bench, the first open benchmark evaluating how accurately LLMs can automate privacy impact assessments using 73 curated federal PIAs.

PIA-Bench is the first open benchmark for evaluating large language models on real-world privacy impact assessments (PIAs). The authors audited 499 expert-authored PIAs published by US federal agencies and curated 73 structured PIAs comprising 451 privacy risk items and 831 mitigation items. Off-the-shelf LLMs were found to produce meaningful assessments while identifying clear avenues for improvement. The paper calls for domain-specific LLM agent workflows, accountable LLM infrastructure, and new quality standards for PIAs.

arXiv cs.CR·Sep 11, 08:16 UTC · 5d agoResearch1

Meta AI builds detailed profiles of children from years of family posts

Meta AI suggested questions about a child and assembled detailed family profiles from years of Facebook posts, including a photo deleted years ago.

A mother reported that Meta AI on Facebook suggested the question 'Who is the child passenger?' and then aggregated her children's names, birth dates, videos, and a photo she had deleted years ago. The assistant also pieced together old posts to pinpoint her home location when prompted with 'Where does Kalie Robins live?'. Meta admitted the prompt 'never should have' appeared and said it fixed the suggestion issue, while noting the data came from posts the asker could already access. The article situates this among prior Meta AI privacy failures, including publicly shared chats and a bug exposing private conversations via guessable IDs.

Malwarebytes Labs·Sep 15, 09:44 UTC · 1d agoAI safety & security

Trust-Aware Adaptive Disclosure for Inference Privacy Preservation in Multi-Agent Networks

Researchers propose a trust-aware privacy framework for multi-agent systems that adapts message disclosure to reduce goal inference attacks.

The cs.CR paper addresses privacy-preserving consensus in networked multi-agent systems where observing adversaries attempt to infer each agent's hidden goal from its messages. A Trust-Aware Privacy Control framework uses a trust-dependent stochastic policy to adapt information release, trading off consensus performance and privacy. Experiments show reduced adversarial goal inference accuracy versus representative baselines while maintaining competitive consensus utility, with relevance to deployments such as healthcare management and smart grids.

arXiv cs.CR·Sep 4, 16:44 UTC · 11d agoResearch

Memory-Efficient Designs for Word-Wise Universal Fully Homomorphic Encryption

BXT framework mitigates FHE memory bottlenecks via ciphertext compression, serialization, delayed seeding, and digit pruning, achieving up to 3.8x CNN inference speedup.

A new paper proposes BXT, an optimization framework for word-wise Universal Fully Homomorphic Encryption that targets the memory bottleneck rather than compute. It combines four techniques: ciphertext compression via seed regeneration, bit-packed ciphertext serialization for L2-to-L1 transfers, delayed PRNG-heavy offline seed generation across aggregated operations, and fault-aware ciphertext digit pruning. On CNN inference, the BXT-CSO50 configuration achieves up to 3.8x speedup over a 100x GPU baseline with under 1% accuracy loss at 50% comparison precision.

arXiv cs.CR·Sep 4, 06:03 UTC · 12d agoResearch

Delaware Consumer Privacy and Data-Breach Law Updates

Delaware's governor signed HB 380 and HB 381 amending the state privacy act and breach notification law.

On September 2, 2026, Delaware's Governor signed House Bill 380 and HB 381. HB 380 amends the Delaware Personal Data Privacy Act (DPDPA), enacted in 2023 and effective January 1, 2025. HB 381 separately amends Delaware's computer security breach notification law. Joseph J. Lazzarotti of JacksonLewis summarizes the changes.

DataBreaches.net·Sep 13, 14:50 UTC · 2d agoPolicy & legal

Meta Patents AI Glasses to Use Facial Recognition to Identify People, Make Highlight Reels of Your Dinner Party

Meta filed a patent for AI glasses that identify people via facial recognition and auto-generate highlight reels of events like dinner parties.

A newly published Meta patent describes smartglasses that use facial recognition to detect people in frame, capture video clips of their actions, and compile highlight reels. The filing signals Meta's continued, controversial push to combine facial recognition with its AI glasses line. The patent was published Thursday and offers granular detail on Meta's product plans, though it does not confirm a shipping feature.

404 Media·Aug 14, 14:17 UTC · Aug 14, 2026AI industry

Subgroup Membership Inference Audits of Differentially Private Synthetic Text

Audits of 32 differentially private synthetic-text releases show subgroup membership leakage is concentrated in few records and systematically underestimated by average-case attacks.

The paper defines a subgroup-targeted membership inference game in which the target pool is an explicit parameter, to audit residual leakage in differentially private synthetic text releases. The audit instantiates 32 proxies across four datasets, three generators (DP-SGD fine-tuning, API-based prompting, and activation steering), and five privacy budgets. DP substantially reduces average leakage at every budget, but remaining leakage is concentrated: roughly a tenth of records carries about 40% of it, and the noise removes more measured leakage from random records than from high-risk ones. Which records leak depends on the release mechanism, so record-level risk cannot be assessed independently of the release.

arXiv cs.CR·Sep 9, 07:56 UTC · 7d agoResearch

ICO Urges Police to Improve Data Governance in Facial Recognition Rollouts

The UK's ICO urged police forces deploying facial recognition to strengthen data governance and follow the regulator's published recommendations.

The UK Information Commissioner's Office called on police forces using facial recognition to improve their data governance practices. The privacy watchdog urged forces to follow its published recommendations when rolling out the technology. The intervention reflects ongoing regulatory scrutiny of law enforcement biometric surveillance in the UK.

Infosecurity Magazine·Aug 19, 09:30 UTC · 28d agoPolicy & legal

Privacy-enhanced federated learning via asynchronous aggregation and local differential perturbation

Federated learning framework combining dynamic differential privacy, homomorphic encryption, and local DP retains 82.6% accuracy at epsilon 0.1 while cutting communication 21.3%.

The paper proposes a privacy-enhanced federated learning framework integrating Dynamic Differential Privacy, lightweight Homomorphic Encryption, and Local Differential Privacy during training. An asynchronous aggregation strategy with version control supports distributed training in asynchronous environments. On CIFAR-10 and Purchase-100, the method maintains up to 82.6% classification accuracy under stringent privacy constraints (epsilon = 0.1) and reduces communication overhead by 21.3% versus FedAvg.

arXiv cs.AI / cs.LG / cs.CL·Sep 14, 17:12 UTC · 1d agoAI research

The AI Supply Chain Has a Security Problem, and Much of It Is Sitting on the Open Internet

Researchers counted 36,769 publicly reachable self-hosted AI endpoints, only about 2% behind HTTP authentication, exposing Ollama, vLLM, and Flowise to abuse.

A Mysterium VPN study found 36,769 self-hosted AI endpoints reachable through internet scanning, with only 2.02% returning an HTTP authentication challenge. Open WebUI accounted for 18,529 reachable instances, Ollama for 6,935 fingerprinted hosts, and 5,223 agent-builder and workflow platforms were exposed, often holding API keys, database credentials, and other secrets. The report highlights LLMjacking risk from exposed Ollama APIs, a critical Flowise bug (CVE-2026-40933), leaked n8n tokens, and prior SentinelOne/Censys research finding roughly 175,000 exposed Ollama hosts in 130 countries.

Security Affairs·Sep 11, 17:27 UTC · 4d agoAI safety & securityCVE-2026-409331

AVP-Inspect: Coordinated Cyber-Physical Testing for Privacy Analysis of COTS Apple Vision Pro Applications

AVP-Inspect automated testing finds 58% of 324 Apple Vision Pro apps show privacy violations, with over 60% of network traffic flows undisclosed.

Researchers built AVP-Inspect, a dynamic analysis framework combining custom hardware device control, 3D UI exploration, and a unified privacy taxonomy for Apple Vision Pro. Testing 324 App Store apps for 20 minutes each found 188 (58.0%) with at least one privacy violation. More than 60% of observed network traffic flows were not properly disclosed, extending prior XR privacy work beyond Android-based devices such as Meta Quest.

arXiv cs.CR·Sep 8, 01:24 UTC · 8d agoResearch1

When AI Agents Go Rogue: Agent Session Smuggling Attack in A2A Systems

Unit 42 unveils agent session smuggling, where a rogue AI agent hides covert instructions in established Agent2Agent (A2A) protocol sessions to manipulate victim agents.

Palo Alto Networks Unit 42 discovered agent session smuggling, a new attack technique in which a malicious AI agent exploits an established cross-agent session under the Agent2Agent (A2A) protocol to send covert instructions hidden among benign client requests and server responses. The technique leverages the implicit trust agents place in collaborating agents and the stateful, multi-turn nature of A2A sessions; the researchers stress it affects any stateful protocol, not an A2A flaw. Unlike one-shot data-based attacks, a rogue agent can converse, adapt and build false trust over multiple interactions. Proposed mitigations include human-in-the-loop enforcement, cryptographically signed AgentCards for remote agent verification, and context-grounding to detect injected instructions.

Palo Alto Unit 42·Aug 17, 12:32 UTC · 29d agoAI safety & security2

GraphProfiler: Source-Linked Sensitive Attribute Inference via Personal Knowledge Graphs

GraphProfiler links LLM attribute inferences to source posts via personal knowledge graphs, enabling targeted redaction of privacy-leaking content.

GraphProfiler represents a user's post history as a source-linked personal knowledge graph where nodes and edges trace back to originating posts, making LLM-based attribute inference auditable. It reaches 86.7% attack success rate on the eight-attribute SynthPAI benchmark and 84.6% on PANDORA, within two points of strong text-only baselines, while citing supporting evidence for over 98% of predictions. Ablation experiments show removing cited posts reduces attack success substantially more than removing random posts, supporting targeted privacy mitigation.

arXiv cs.CR·Sep 11, 05:13 UTC · 5d agoResearch1

Risky Bulletin: Slovakia finds Russian backdoor in traffic speed cameras

Slovakia's NBU found an SMS-triggered backdoor in Russian-made NERO R-ONE traffic cameras, pausing a 279-unit deployment.

Slovakia's national security service NBU issued an alert against NERO R-ONE high-speed traffic cameras after finding a backdoor that grants shell and network access via SMS from hardcoded Russian phone numbers. The cameras are a rebranded version of the Russian CORDON PRO.M model by St. Petersburg firm Semicon, purchased via a Cyprus shell company under a €30 million EU-funded project. The report also found SecureBoot disabled, vulnerable web management, and unauthenticated live streams; the Interior Ministry paused deployment of 279 cameras pending independent assessment.

Risky Business News·Aug 19, 04:52 UTC · 28d agoThreat actor in the wild1

Privacy-Aligned Personalized Federated Learning with Compact Adaptation and Variable-Length Gaussian Communication

Paper releases a private client context once and confines adaptation to coefficients, matching full-model differential privacy with 2.67x less uplink on CIFAR-10.

The paper addresses the dimensionality misalignment between record-level differential privacy and low-dimensional client variation in personalized federated learning by releasing a private client context once and restricting repeated adaptation to a fixed coefficient space. A variable-length quantized Gaussian mechanism lets quantization error itself serve as the required privacy perturbation. On MNIST and CIFAR-10, the design matches or outperforms full-model private adaptation across privacy budgets and client heterogeneity while cutting protected uplink 2.67x at epsilon=16 on CIFAR-10.

arXiv cs.AI / cs.LG / cs.CL·Sep 14, 17:48 UTC · 1d agoAI research1

Keepnet launches free SMS/Call Reporter for iOS

Keepnet launched a free iOS app, SMS/Call Reporter, letting users one-tap report smishing and vishing into corporate incident response pipelines.

Keepnet released the free SMS/Call Reporter app for iOS, letting users report suspicious SMS and voice phishing with one tap. For enterprise customers, reports flow into Keepnet Incident Responder alongside email phishing reports. The company cites Verizon 2026 DBIR data showing mobile phishing simulations achieve a 40% higher median click rate than email, and FBI IC3 2025 counted $798 million in smishing and vishing losses. An Android version is planned.

Help Net Security·Sep 2, 00:00 UTC · 14d agoTools

Reverse-Lookup Service Exposed Millions of Photos of People’s Faces

People-search service ClarityCheck exposed a database with more than 9 million facial image files despite marketing its reverse lookup as private and secure.

WIRED reports that ClarityCheck, a people-search tool offering reverse image lookup, left a database containing more than 9 million image files of people's faces exposed. The company markets the service as private and secure. The exposure affects millions of individuals whose facial photos could be linked to their identities.

WIRED · Security·Aug 19, 10:00 UTC · 28d agoData breach

PHAT: PHotonic Accelerator for TFHE

PHAT photonic accelerator using optically addressed phase-change memory speeds TFHE bootstrapping FFTs 2.14x-5.10x over the prior ASIC accelerator.

Researchers propose PHAT, an electro-photonic accelerator for TFHE fully homomorphic encryption built on optically addressed phase-change memory (OPCM) processing-in-memory. The architecture adds OPCM-based FFT units, a twiddle-stationary dataflow, and a scheduling mechanism to maximize FFT utilization for TFHE bootstrapping. It achieves 2.14x-5.10x speedups across four real-world TFHE workloads versus the state-of-the-art ASIC accelerator, improving feasibility of privacy-preserving computation in the cloud.

arXiv cs.CR·Sep 10, 14:30 UTC · 5d agoResearch

Personal Info Possibly Compromised at Japan’s Digital Agency

Japan's Digital Agency says unauthorized access to a network system may have compromised personal data of about 246,000 government employees.

Japan's Digital Agency reported that approximately 246,000 sets of personal information, including names and email addresses of government employees, may have been compromised through unauthorized access to a network system operated by the agency. The agency said no secondary damage, such as misuse of the potentially breached data, has been identified so far.

DataBreaches.net·Sep 11, 16:06 UTC · 4d agoData breach