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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
To Share or Not to Share in Client-Side Encrypted Clouds
Duane Wilson, Giuseppe Ateniese · 2014-04-10 · via cs.CR updates on arXiv.org

With the advent of cloud computing, a number of cloud providers have arisen to provide Storage-as-a-Service (SaaS) offerings to both regular consumers and business organizations. SaaS (different than Software-as-a-Service in this context) refers to an architectural model in which a cloud provider provides digital storage on their own infrastructure. Three models exist amongst SaaS providers for protecting the confidentiality data stored in the cloud: 1) no encryption (data is stored in plain text), 2) server-side encryption (data is encrypted once uploaded), and 3) client-side encryption (data is encrypted prior to upload). This paper seeks to identify weaknesses in the third model, as it claims to offer 100% user data confidentiality throughout all data transactions (e.g., upload, download, sharing) through a combination of Network Traffic Analysis, Source Code Decompilation, and Source Code Disassembly. The weaknesses we uncovered primarily center around the fact that the cloud providers we evaluated were each operating in a Certificate Authority capacity to facilitate data sharing. In this capacity, they assume the role of both certificate issuer and certificate authorizer as denoted in a Public-Key Infrastructure (PKI) scheme - which gives them the ability to view user data contradicting their claims of 100% data confidentiality. We have collated our analysis and findings in this paper and explore some potential solutions to address these weaknesses in these sharing methods. The solutions proposed are a combination of best practices associated with the use of PKI and other cryptographic primitives generally accepted for protecting the confidentiality of shared information.