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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
Preventing Identity Attacks in RFID Backscatter Communica...
Ahsan Mehmood, Waqas Aman, M. Mahboob Ur Rahman, M. A. Imran, Qa · 2020-09-01 · via cs.CR updates on arXiv.org

This work considers identity attack on a radio-frequency identification (RFID)-based backscatter communication system. Specifically, we consider a single-reader, single-tag RFID system whereby the reader and the tag undergo two-way signaling which enables the reader to extract the tag ID in order to authenticate the legitimate tag (L-tag). We then consider a scenario whereby a malicious tag (M-tag)---having the same ID as the L-tag programmed in its memory by a wizard---attempts to deceive the reader by pretending to be the L-tag. To this end, we counter the identity attack by exploiting the non-reciprocity of the end-to-end channel (i.e., the residual channel) between the reader and the tag as the fingerprint of the tag. The passive nature of the tag(s) (and thus, lack of any computational platform at the tag) implies that the proposed light-weight physical-layer authentication method is implemented at the reader. To be concrete, in our proposed scheme, the reader acquires the raw data via two-way (challenge-response) message exchange mechanism, does least-squares estimation to extract the fingerprint, and does binary hypothesis testing to do authentication. We also provide closed-form expressions for the two error probabilities of interest (i.e., false alarm and missed detection). Simulation results attest to the efficacy of the proposed method.