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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
Ghost-in-the-Wireless: Energy Depletion Attack on ZigBee
Devu Manikantan Shila, Xianghui Cao, Yu Cheng, Zequ Yang, Yang Z · 2014-10-07 · via cs.CR updates on arXiv.org

ZigBee has been recently drawing a lot of attention as a promising solution for ubiquitous computing. The ZigBee devices are normally resource-limited, making the network susceptible to a variety of security threats. This paper presents a severe attack on ZigBee networks termed as ghost, which leverages the underlying vulnerabilities of the IEEE 802.15.4 security suites to deplete the energy of the devices. We manifest that the impact of ghost is severe as it can reduce the lifetime of devices from years to days and facilitate a variety of threats including denial of service and replay attacks. We highlight that merely deploying a standard suite of advanced security techniques does not necessarily guarantee improved security, but instead might be leveraged by adversaries to cause severe disruption in the network. We propose several recommendations on how to localize and withstand the ghost and other related attacks in ZigBee networks. Extensive simulations are provided to show the impact of the ghost and the performance of the proposed recommendations. Moreover, physical experiments also have been conducted and the observations confirm the severity of the impact by the ghost attack. We believe that the presented work will aid the researchers to improve the security of ZigBee further.