惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

D
DataBreaches.Net
N
Netflix TechBlog - Medium
P
Proofpoint News Feed
D
Docker
J
Java Code Geeks
L
LangChain Blog
Microsoft Security Blog
Microsoft Security Blog
The GitHub Blog
The GitHub Blog
I
InfoQ
Stack Overflow Blog
Stack Overflow Blog
云风的 BLOG
云风的 BLOG
Engineering at Meta
Engineering at Meta
MongoDB | Blog
MongoDB | Blog
月光博客
月光博客
T
Tailwind CSS Blog
M
MIT News - Artificial intelligence
Blog — PlanetScale
Blog — PlanetScale
Google DeepMind News
Google DeepMind News
腾讯CDC
罗磊的独立博客
U
Unit 42
爱范儿
爱范儿
Vercel News
Vercel News
MyScale Blog
MyScale Blog

cs.SI updates on arXiv.org

Hiding in Plain Sight: Finding MAHA on Reddit Prism: Structural Symmetry Scanning via Duality-Constrained Laplacian Projection MV-Gate: Insider Threat Detection via Multi-View Behavioral Statistics and Semantic Modeling Algorithmic Cultivation: How Social Media Feeds Shape User Language Universal Dynamics of Punctuated Progress AI-Mediated Communication Can Steer Collective Opinion CitePrism: Human-in-the-Loop AI for Citation Auditing and Editorial Integrity Explainable Detection of Depression Status Shifts from User Digital Traces Can Visual Mamba Improve AI-Generated Image Detection? An In-Depth Investigation ScioMind: Cognitively Grounded Multi-Agent Social Simulation with Anchoring-Based Belief Dynamics and Dynamic Profiles Humanwashing -- It Should Leave You Feeling Dirty When Do LLMs Generate Realistic Social Networks? A Multi-Dimensional Study of Culture, Language, Scale, and Method Moltbook Moderation: Uncovering Hidden Intent Through Multi-Turn Dialogue Linking Extreme Discourse to Structural Polarization in Signed Interaction Networks Predicting Channel Closures in the Lightning Network with Machine Learning Latent Causal Void: Explicit Missing-Context Reconstruction for Misinformation Detection Predictive Maps of Multi-Agent Reasoning: A Successor-Representation Spectrum for LLM Communication Topologies Large Language Models for Causal Relations Extraction in Social Media: A Validation Framework for Disaster Intelligence When Can Digital Personas Reliably Approximate Human Survey Findings? RAwR: Role-Aware Rewiring via Approximate Equitable Partition GravityGraphSAGE: Link Prediction in Directed Attributed Graphs Structure-Centric Graph Foundation Model via Geometric Bases Attention-based graph neural networks: a survey When AI Meets Science: Research Diversity, Interdisciplinarity, Visibility, and Retractions across Disciplines in a Global Surge Scalable inference of spatial regions and temporal signatures from time series Can LLMs Emulate Human Belief Dynamics? Predicting Post Virality with Temporal Cross-Attention over Trend Signals H3: A Healthcare Three-Hop Index for Physician Referral Network Prediction Dynamic Graph with Similarity-Aware Attention Graph Neural Network for Recommender Systems Spectral Graph Sparsification Preserves Representation Geometry in Graph Neural Networks
Facebook Use of Sensitive Data for Advertising in Europe
José González Cabañas, Ángel Cuevas, Rubén Cuevas · 2018-02-14 · via cs.SI updates on arXiv.org

The upcoming European General Data Protection Regulation (GDPR) prohibits the processing and exploitation of some categories of personal data (health, political orientation, sexual preferences, religious beliefs, ethnic origin, etc.) due to the obvious privacy risks that may be derived from a malicious use of such type of information. These categories are referred to as sensitive personal data. Facebook has been recently fined EUR 1.2M in Spain for collecting, storing and processing sensitive personal data for advertising purposes. This paper quantifies the portion of Facebook users in the European Union (EU) who are labeled with interests linked to sensitive personal data. The results of our study reveal that Facebook labels 73% EU users with sensitive interests. This corresponds to 40% of the overall EU population. We also estimate that a malicious third-party could unveil the identity of Facebook users that have been assigned a sensitive interest at a cost as low as EUR 0.015 per user. Finally, we propose and implement a web browser extension to inform Facebook users of the sensitive interests Facebook has assigned them.