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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
LightIoT: Lightweight and Secure Communication for Energy...
Mian Ahmad Jan, Fazlullah Khan, Spyridon Mastorakis, Muhammad Ad · 2021-04-30 · via cs.CR updates on arXiv.org

Internet of Things (IoT) is considered as a key enabler of health informatics. IoT-enabled devices are used for in-hospital and in-home patient monitoring to collect and transfer biomedical data pertaining to blood pressure, electrocardiography (ECG), blood sugar levels, body temperature, etc. Among these devices, wearables have found their presence in a wide range of healthcare applications. These devices generate data in real-time and transmit them to nearby gateways and remote servers for processing and visualization. The data transmitted by these devices are vulnerable to a range of adversarial threats, and as such, privacy and integrity need to be preserved. In this paper, we present LightIoT, a lightweight and secure communication approach for data exchanged among the devices of a healthcare infrastructure. LightIoT operates in three phases: initialization, pairing, and authentication. These phases ensure the reliable transmission of data by establishing secure sessions among the communicating entities (wearables, gateways and a remote server). Statistical results exhibit that our scheme is lightweight, robust, and resilient against a wide range of adversarial attacks and incurs much lower computational and communication overhead for the transmitted data in the presence of existing approaches.