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

G
Google Developers Blog
宝玉的分享
宝玉的分享
月光博客
月光博客
B
Blog
云风的 BLOG
云风的 BLOG
Google DeepMind News
Google DeepMind News
Engineering at Meta
Engineering at Meta
aimingoo的专栏
aimingoo的专栏
N
Netflix TechBlog - Medium
博客园_首页
GbyAI
GbyAI
人人都是产品经理
人人都是产品经理
A
About on SuperTechFans
Y
Y Combinator Blog
L
LangChain Blog
有赞技术团队
有赞技术团队
D
Docker
爱范儿
爱范儿
博客园 - 司徒正美
H
Hackread – Cybersecurity News, Data Breaches, AI and More
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
酷 壳 – CoolShell
酷 壳 – CoolShell
Microsoft Security Blog
Microsoft Security Blog
D
DataBreaches.Net

cs.HC updates on arXiv.org

From Prompt to Service: An SLM-Based Agent Orchestration Gateway for AI-Driven Virtual Worlds What LLMs Must Forget to Teach Effectively: A DIY Approach to Premodern Japanese Language Pedagogy Quantitative Movement Testing: Measuring Patient Movements from a Single Smartphone Video Vision-Language Models Suppress Female Representations Under Ambiguous Input The New Social Image: How AI Competency and AI Proactivity Influence Self- and Peer-Perceptions in the Workplace TUX: Measuring Human--AI Tacit Understanding LLUMI: Improving LLM Writing Assistance for Mental Health Support with Online Community Feedback VideoFDB: Evaluating Full-Duplex Vision-Speech Capabilities in Conversational Agents Label Over Logic? How Source Cues Bias Human Fallacy Judgments More Than LLMs Inform, Coach, Relate, Listen: Auditing LLM Caregiving Support Roles How Coding Agents Fail Their Users: A Large-Scale Analysis of Developer-Agent Misalignment in 20,574 Real-World Sessions MetaRanker: Human-in-the-loop Active Ranking for Metalens Image Quality Analyzing Persona Effects in Generated Explanations from Multimodal LLM Agents in Urban Perception First head-to-head comparison of agentic AI applied to the analysis of simulated data of the Einstein Telescope Granuscore: A Reference-Free Measure of Granularity for Text Analysis and Question Answering The Timing Dependencies of Trust: Speed, Accuracy, and cBCI Neuro-Decoupling in Human-AI Teams Bayesian Distributional Models of Executive Functioning Visual Matters: Connecting Aesthetic Appeal and Production Quality of Photos, Infographics and Data Visualizations to Credibility of Social Media Posts Data-driven Head Motion Generation through Natural Gaze-Head Coordination Agreement Metrics for LLM-as-Judge Evaluation: What to Report and Why Perceptually Lossless Tactile Texture Synthesis with Compact Spectral Envelope Models MambaGaze: Bidirectional Mamba with Explicit Missing Data Modeling for Cognitive Load Assessment from Eye-Gaze Tracking Data CogAdapt: Transferring Clinical ECG Foundation Models to Wearable Cognitive Load Assessment via Lead Adaptation Augmented Analytics and Decision Quality: The Role of Trust among Non-Technical BI Users Faster Completion, Less Learning: Generative AI Reduced Study Time on Math Problems and the Knowledge They Build PaintCopilot: Modeling Painting as Autonomous Artistic Continuation Personality Engineering with AI Agents: A New Methodology for Negotiation Research PULSE: Agentic Investigation with Passive Sensing for Proactive Intervention in Cancer Survivorship Access Timing as Scaffolding: A Reinforcement Learning Approach to GenAI in Education MAPLE: Self-Supervised Learning-Enhanced Nonlinear Dimensionality Reduction for Visual Analysis
Why is My Secret Leaked? Discovering Vulnerabilities in D...
Andrei Bytes, Jay Prakash, Jianying Zhou, Tony Q. S. Quek · 2020-02-08 · via cs.HC updates on arXiv.org

The number of active users of Wi-Fi Direct Device-to-Device file sharing applications on Android has exceeded 1.8 billion. Wi-Fi Direct, also known as Wi-Fi P2P, is commonly used for peer-to-peer, high-speed file transfer between mobile devices, as well as a close proximity connection mode for wireless cameras, network printers, TVs and other IoT and mobile devices. For its end users, such type of direct file transfer does not incur cellular data charges. However, despite the popularity of such applications, we observe that the software vendors tend to prioritize the ease of user flow over the security in their implementations, which leads to serious security flaws. We perform a comprehensive security analysis in the context of security and usability and report our findings in the form of 17 Common Vulnerabilities and Exposures (CVE) which have been disclosed to the corresponding vendors. To address the similar flaws at the early stage of the application design, we propose a joint consideration of security and usability for such applications and their protocols that can be visualized in form of a customised User Journey Map (UJM).