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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
A Practical System for Guaranteed Access in the Presence ...
Yi-Hsuan Kung, Taeho Lee, Po-Ning Tseng, Hsu-Chun Hsiao, Tiffany · 2015-09-08 · via cs.CR updates on arXiv.org

With the growing incidents of flash crowds and sophisticated DDoS attacks mimicking benign traffic, it becomes challenging to protect Internet-based services solely by differentiating attack traffic from legitimate traffic. While fair-sharing schemes are commonly suggested as a defense when differentiation is difficult, they alone may suffer from highly variable or even unbounded waiting times. We propose RainCheck Filter (RCF), a lightweight primitive that guarantees bounded waiting time for clients despite server flooding without keeping per-client state on the server. RCF achieves strong waiting time guarantees by prioritizing clients based on how long the clients have waited-as if the server maintained a queue in which the clients lined up waiting for service. To avoid keeping state for every incoming client request, the server sends to the client a raincheck, a timestamped cryptographic token that not only informs the client to retry later but also serves as a proof of the client's priority level within the virtual queue. We prove that every client complying with RCF can access the server in bounded time, even under a flash crowd incident or a DDoS attack. Our large-scale simulations confirm that RCF provides a small and predictable maximum waiting time while existing schemes cannot. To demonstrate its deployability, we implement RCF as a Python module such that web developers can protect a critical server resource by adding only three lines of code.