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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
A comprehensive survey on RPL routing-based attacks, defe...
Anil K Prajapati, Emmanuel S Pilli, Ramesh B Battula, Vijay Vara · 2025-01-19 · via cs.CR updates on arXiv.org

The Internet of Things (IoT) is a network of digital devices like sensors, processors, embedded and communication devices that can connect to and exchange data with other devices and systems over the internet. IoT devices have limitations on power, memory, and computational resources. Researchers have developed the IPv6 Over Low-power Wireless Personal Area Network (6LoWPAN) protocols to provide wireless connectivity among these devices while overcoming the constraints on resources. 6LoWPAN has been approved subsequently by the Internet Engineering Task Force (IETF). The IETF Routing Over Low-power and Lossy Networks (ROLL) standardized the Routing Protocol for LLNs known as RPL (IETF RFC 6550), which is part of the 6LoWPAN stack. However, IoT devices are vulnerable to various attacks on RPL-based routing. This survey provides an in depth study of existing RPL-based attacks and defense published from year 2011 to 2024 from highly reputed journals and conferences. By thematic analysis of existing routing attacks on RPL, we developed a novel attack taxonomy which focuses on the nature of routing attacks and classifies them into 12 major categories. Subsequently, the impact of each attack on the network is analyzed and discussed real life scenarios of these attacks. Another contribution of this survey proposed a novel taxonomy for classification of defense mechanisms into 8 major categories against routing attacks based on type of defense strategy. The detailed analysis of each defense mechanism with real life applicability is explained. Furthermore, evaluation tools such as testbeds and simulators for RPL-based attack and defense are discussed and critically analyzed in terms of real world applicability. Finally, open research challenges are presented on the basis of research gaps of existing literature along with research directions for practitioners and researchers.