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cs.CR updates on arXiv.org

On the Security of Research Artifacts SafeHarbor: Hierarchical Memory-Augmented Guardrail for LLM Agent Safety 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 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
Topological and Temporal Stability Analysis of the Lightn...
[Submitted on 10 Dec 2025 (v1), last revised 7 Aug 2026 (this ve · 2025-12-11 · via cs.CR updates on arXiv.org

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Abstract:The Lightning Network (LN) is the most prominent payment channel network built atop Bitcoin, designed to enable scalable, low-cost off-chain transactions. Understanding its structural evolution and temporal stability is critical for routing optimization, liquidity allocation, and infrastructure robustness. Leveraging a validated dataset of LN topology snapshots spanning 2019-2023, we compute a set of network-science metrics under directed, undirected, unweighted, capacity-weighted, and routing-aware graph representations. To our knowledge, this is the first longitudinal multi-representation temporal stability analysis of the Lightning Network combining topological, distributional, and routing-equivalent persistence metrics over a 5-year validated snapshot dataset. Developed analytical framework reveals a network undergoing gradual structural sparsification and increasing modularization: density, clustering, and global efficiency decline over time, while community fragmentation and centralization persist. However, distributional and observed operational characteristics remain remarkably stable.

Submission history

From: Danila Valko [view email]
[v1] Wed, 10 Dec 2025 17:50:52 UTC (1,241 KB)
[v2] Fri, 7 Aug 2026 16:50:53 UTC (1,141 KB)