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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
Designing a Layered Framework to Secure Data via Improved...
Hojjat Farshadinia, Ali Barati, Hamid Barati · 2025-09-02 · via cs.CR updates on arXiv.org

This paper presents a novel multi-layered hybrid security approach aimed at enhancing lightweight encryption for IoT-Cloud systems. The primary goal is to overcome limitations inherent in conventional solutions such as TPA, Blockchain, ECDSA and ZSS which often fall short in terms of data protection, computational efficiency and scalability. Our proposed method strategically refines and integrates these technologies to address their shortcomings while maximizing their individual strengths. By doing so we create a more reliable and high-performance framework for secure data exchange across heterogeneous environments. The model leverages the combined potential of emerging technologies, particularly Blockchain, IoT and Cloud computing which when effectively coordinated offer significant advancements in security architecture. The proposed framework consists of three core layers: (1) the H.E.EZ Layer which integrates improved versions of Hyperledger Fabric, Enc-Block and a hybrid ECDSA-ZSS scheme to improve encryption speed, scalability and reduce computational cost; (2) the Credential Management Layer independently verifying data integrity and authenticity; and (3) the Time and Auditing Layer designed to reduce traffic overhead and optimize performance across dynamic workloads. Evaluation results highlight that the proposed solution not only strengthens security but also significantly improves execution time, communication efficiency and system responsiveness, offering a robust path forward for next-generation IoT-Cloud infrastructures.