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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
An Analysis of Chinese Search Engine Filtering
Tao Zhu, Christopher Bronk, Dan S. Wallach · 2011-07-20 · via cs.CR updates on arXiv.org

The imposition of government mandates upon Internet search engine operation is a growing area of interest for both computer science and public policy. Users of these search engines often observe evidence of censorship, but the government policies that impose this censorship are not generally public. To better understand these policies, we conducted a set of experiments on major search engines employed by Internet users in China, issuing queries against a variety of different words: some neutral, some with names of important people, some political, and some pornographic. We conducted these queries, in Chinese, against Baidu, Google (including google.cn, before it was terminated), Yahoo!, and Bing. We found remarkably aggressive filtering of pornographic terms, in some cases causing non-pornographic terms which use common characters to also be filtered. We also found that names of prominent activists and organizers as well as top political and military leaders, were also filtered in whole or in part. In some cases, we found search terms which we believe to be "blacklisted". In these cases, the only results that appeared, for any of them, came from a short "whitelist" of sites owned or controlled directly by the Chinese government. By repeating observations over a long observation period, we also found that the keyword blocking policies of the Great Firewall of China vary over time. While our results don't offer any fundamental insight into how to defeat or work around Chinese internet censorship, they are still helpful to understand the structure of how censorship duties are shared between the Great Firewall and Chinese search engines.