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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
Enhancing Wireless Sensor Network Security through Integr...
Syed Atif Ali, Salwa Din · 2024-12-31 · via cs.CR updates on arXiv.org

Wireless Sensor Networks (WSNs) continue to experience rapid developments and integration into modern-day applications. Overall, WSNs collect and process relevant data through sensors or nodes and communicate with different networks for superior information management. Nevertheless, a primary concern relative to WSNs is security. Considering the high constraints on throughput, battery, processing power, and memory, typical security procedures present limitations for application in WSNs. This research focuses on the integration of WSNs with the cloud platform, specifically to address these security risks. The cloud platform also adopts a security-driven approach and has attracted many applications across various sectors globally. This research specifically explores how cloud computing could be exploited to impede Denial of Service attacks from endangering WSNs. WSNs are now deployed in various low-powered applications, including disaster management, homeland security, battlefield surveillance, agriculture, and the healthcare industry. WSNs are distinguished from traditional networks by the numerous wireless connected sensors being deployed to conduct an assigned task. In testing scenarios, the size of WSNs ranges from a few to several thousand. The overarching requirements of WSNs include rapid processing of collected data, low-cost installation and maintenance, and low latency in network operations. Given that a substantial amount of WSN applications are used in high-risk and volatile environments, they must effectively address security concerns. This includes the secure movement, storage, and communication of data through networks, an environment in which WSNs are notably vulnerable. The limitations of WSNs have meant that they are predominantly used in unsecured applications despite positive advancements. This study explores methods for integrating the WSN with the cloud.