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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
Private Web Search with an Expected Constant Round
Myungsun Kim · 2016-04-11 · via cs.CR updates on arXiv.org

Web searching is becoming an essential activity because it is often the most effective and convenient way of finding information. However, a Web search can be a threat to the privacy of the searcher because the queries may reveal sensitive information about the searcher. Private Web search (PWS) solutions allow users to find information on the Internet while preserving their privacy. Here, privacy means maintaining the confidentiality of the identity of the communicating users. According to their underlying technology, existing PWS solutions can be divided into three types: proxy-based solutions, obfuscation-based solutions, and cryptography-based solutions. Of these, cryptography-based PWS (CB-PWS) systems are particularly interesting because they provide strong privacy guarantees in the cryptographic sense. In this paper, we present a round-efficient CB-PWS protocol that preserves computational efficiency compared to other known CB-PWS systems. Assuming a broadcast channel, our protocol is a \emph{four-round} cryptographic scheme that requires $O(n)$ communication complexity. However, if only point-to-point interaction is available, with the users emulating the broadcast channel, our protocol requires an expected $O(1)$-round complexity and the same computation and communication overhead. Further analyzing the efficiency of our protocol shows that our proposal requires only $3n$ modular exponentiations for $n$ users. To evaluate the security of our protocol, we demonstrate that our construction is secure in terms of a semi-honest model. We then discuss how to enhance its security to render it secure in the presence of malicious adversaries. We provide a specific protocol for managing users' groups, which is also an advantage over existing systems.