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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
An Efficient, Secure and Trusted Channel Protocol for Avi...
Raja Naeem Akram, Konstantinos Markantonakis, Keith Mayes, Pierr · 2016-08-15 · via cs.CR updates on arXiv.org

Avionics networks rely on a set of stringent reliability and safety requirements. In existing deployments, these networks are based on a wired technology, which supports these requirements. Furthermore, this technology simplifies the security management of the network since certain assumptions can be safely made, including the inability of an attacker to access the network, and the fact that it is almost impossible for an attacker to introduce a node into the network. The proposal for Avionics Wireless Networks (AWNs), currently under development by multiple aerospace working groups, promises a reduction in the complexity of electrical wiring harness design and fabrication, a reduction in the total weight of wires, increased customization possibilities, and the capacity to monitor otherwise inaccessible moving or rotating aircraft parts such as landing gear and some sections of the aircraft engines. While providing these benefits, the AWN must ensure that it provides levels of safety that are at minimum equivalent to those offered by the wired equivalent. In this paper, we propose a secure and trusted channel protocol that satisfies the stated security and operational requirements for an AWN protocol. There are three main objectives for this protocol. First, the protocol has to provide the assurance that all communicating entities can trust each other, and can trust their internal (secure) software and hardware states. Second, the protocol has to establish a fair key exchange between all communicating entities so as to provide a secure channel. Finally, the third objective is to be efficient for both the initial start-up of the network and when resuming a session after a cold and/or warm restart of a node. The proposed protocol is implemented and performance measurements are presented based on this implementation. In addition, we formally verify our proposed protocol using CasperFDR.