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

V
Visual Studio Blog
博客园 - 司徒正美
博客园_首页
Jina AI
Jina AI
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
月光博客
月光博客
I
InfoQ
M
MIT News - Artificial intelligence
T
Tailwind CSS Blog
L
LangChain Blog
Last Week in AI
Last Week in AI
A
About on SuperTechFans
B
Blog
博客园 - 叶小钗
雷峰网
雷峰网
H
Help Net Security
WordPress大学
WordPress大学
大猫的无限游戏
大猫的无限游戏
博客园 - 【当耐特】
云风的 BLOG
云风的 BLOG
Microsoft Azure Blog
Microsoft Azure Blog
小众软件
小众软件
aimingoo的专栏
aimingoo的专栏
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻

cs.CR updates on arXiv.org

Agentic Vulnerability Reasoning on Windows COM Binaries From Beats to Breaches:How Offensive AI Infers Sensitive User Information from Playlists Undetectable Backdoors in Model Parameters: Hiding Sparse Secrets in High Dimensions When Embedding-Based Defenses Fail: Rethinking Safety in LLM-Based Multi-Agent Systems Token-Efficient Change Detection in LLM APIs Selfie-Capture Dynamics as an Auxiliary Signal Against Deepfakes and Injection Attacks for Mobile Identity Verification Trident: Improving Malware Detection with LLMs and Behavioral Features When Alignment Isn't Enough: Response-Path Attacks on LLM Agents RefusalGuard: Geometry-Preserving Fine-Tuning for Safety in LLMs Checkerboard: A Simple, Effective, Efficient and Learning-free Clean Label Backdoor Attack with Low Poisoning Budget Block-wise Codeword Embedding for Reliable Multi-bit Text Watermarking Secret Stealing Attacks on Local LLM Fine-Tuning through Supply-Chain Model Code Backdoors Enhancing Linux Privilege Escalation Attack Capabilities of Local LLM Agents Defusing the Trigger: Plug-and-Play Defense for Backdoored LLMs via Tail-Risk Intrinsic Geometric Smoothing Evaluating Jailbreaking Vulnerabilities in LLMs Deployed as Assistants for Smart Grid Operations: A Benchmark Against NERC Standards Behavioral Canaries: Auditing Private Retrieved Context Usage in RL Fine-Tuning FlexServe: A Fast and Secure LLM Serving System for Mobile Devices with Flexible Resource Isolation Breaking MCP with Function Hijacking Attacks: Novel Threats for Function Calling and Agentic Models Text Steganography with Dynamic Codebook and Multimodal Large Language Model An AI Agent Execution Environment to Safeguard User Data TwoHamsters: Benchmarking Multi-Concept Compositional Unsafety in Text-to-Image Models Fundamental Limitations of Favorable Privacy-Utility Guarantees for DP-SGD Symbolic Guardrails for Domain-Specific Agents: Stronger Safety and Security Guarantees Without Sacrificing Utility Hardening x402: PII-Safe Agentic Payments via Pre-Execution Metadata Filtering QShield: Securing Neural Networks Against Adversarial Attacks using Quantum Circuits Hijacking Text Heritage: Hiding the Human Signature through Homoglyphic Substitution Like a Hammer, It Can Build, It Can Break: Large Language Model Uses, Perceptions, and Adoption in Cybersecurity Operations on Reddit Private Seeds, Public LLMs: Realistic and Privacy-Preserving Synthetic Data Generation One Word at a Time: Incremental Completion Decomposition Breaks LLM Safety Measuring and Exploiting Contextual Bias in LLM-Assisted Security Code Review
Combining Usability and Privacy Protection in Free-Access...
Alejandro Sanchez-Gomez, Jesus Diaz, David Arroyo · 2016-10-27 · via cs.CR updates on arXiv.org

The 21st century belongs to the world of computing, specially as a result of the so-called cloud computing. This technology enables ubiquitous information management and thus people can access all their data from any place and at any time. In this landscape, the emergence of cloud storage has had an important role in the last five years. Nowadays, several free-access public cloud storage services make it possible for users to have a free backup of their assets and to manage and share them, representing a low-cost opportunity for Small and Medium Companies (SME). However, the adoption of cloud storage involves data outsourcing, so a user does not have the guarantee about the way her data will be processed and protected. Therefore, it seems necessary to endow public cloud storage with a set of means to protect users' confidentiality and privacy, to assess data integrity and to guarantee a proper backup of information assets. Along this paper we discuss the main challenges to achieve such a goal, underlining the set of functionalities already implemented in the most popular public cloud storage services.