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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
Effective Data Aggregation in WSN for Enhanced Security a...
B. Murugeshwari, S. Aminta Sabatini, Lovelit Jose, S. Padmapriya · 2023-04-28 · via cs.CR updates on arXiv.org

The two biggest problems with wireless sensor networks are security and energy usage. In sensing devices, malicious nodes could be found in large numbers. The researchers have proposed several methods to find these rogue nodes. To prevent assaults on these networks and data transmission, the data must be secured. Data aggregation aids in reducing the number of messages transmitted within the network, which in turn lowers total network energy consumption. Additionally, when decrypting the aggregated data, the base station can distinguish between encrypted and consolidated analysis based on top of the cryptographic keys. By examining the effectiveness of the data aggregation in this research. To solve the above problem, the system provides a method in which an efficient cluster agent is preferred pedestal on its location at the access point and energy availability. The sensor network's energy consumption is reduced by selecting an effective cluster agent, extending the network's lifespan. The cluster's agent is in indict of compiling data for each member node. The clustering agent validates the data and tosses any errors before aggregation. The clustering agent only aggregates confirmed data. To provide end-to-end anonymity, ElGamal elliptic curve (ECE) encryption is used to secure the client data and reassign the encrypted information en route for the cluster agent. Only the base station (BS) can decrypt the data. Furthermore, an ID-based signature system is utilized to enable authenticity. This research presents a technique for recuperating lost data. The access point employs a cache-based backup system to search for lost data.