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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
SPAM over Internet Telephony and how to deal with it
Andreas U. Schmidt, Nicolai Kuntze, Rachid El Khayari · 2008-06-10 · via cs.CR updates on arXiv.org

In our modern society telephony has developed to an omnipresent service. People are available at anytime and anywhere. Furthermore the Internet has emerged to an important communication medium. These facts and the raising availability of broadband internet access has led to the fusion of these two services. Voice over IP or short VoIP is the keyword, that describes this combination. The advantages of VoIP in comparison to classic telephony are location independence, simplification of transport networks, ability to establish multimedia communications and the low costs. Nevertheless one can easily see, that combining two technologies, always brings up new challenges and problems that have to be solved. It is undeniable that one of the most annoying facet of the Internet nowadays is email spam. According to different sources email spam is considered to be 80 to 90 percent of the email traffic produced. The threat of so called voice spam or Spam over Internet Telephony (SPIT) is even more fatal, for the annoyance and disturbance factor is much higher. As instance an email that hits the inbox at 4 p.m. is useless but will not disturb the user much. In contrast a ringing phone at 4 p.m. will lead to a much higher disturbance. From the providers point of view both email spam and voice spam produce unwanted traffic and loss of trust of customers into the service. In order to mitigate this threat different approaches from different parties have been developed. This paper focuses on state of the art anti voice spam solutions, analyses them and reveals their weak points. In the end a SPIT producing benchmark tool will be introduced, that attacks the presented anti voice spam solutions. With this tool it is possible for an administrator of a VoIP network to test how vulnerable his system is.