Dataset and Codebase for Enhanced Security with Pre-Shared Key Simplicity for Lightweight and Secure IoT–Edge Communication

This repository contains the complete experimental and analytical dataset supporting the study“Lightweight Session-Key Rekeying Framework for Secure IoT–Edge Communication” The artifact demonstrates a secure IoT–Edge communication model using HKDF-SHA256 derived dynamic session keys with AES-GCM authenticated encryption. Experiments were executed on a real-world setup involving ESP32 sensor nodes and a Raspberry Pi 5 edge server with containerized MQTT communication. 📁 Folder Structure 1. PSK EXP/ – Complete baseline PSK-AES-GCM implementation. CLIENT-SIDE/ → ESP32 code, Arduino libraries, raw packet logs. SERVER-SIDE/ → MQTT broker logs, decrypted data, and Docker configuration. 2. DSEKP EXP/ – DSEKP experiment dataset using per-session HKDF keys. CLIENT-SIDE/ → DSEKP-AES-GCM (ESP32 sketch), multiple and single-session test logs. SERVER-SIDE/ → Reliability and 6500-packet analysis results (MATLAB figures and CSV). PSK vs DSEKP ANALYSIS/ – Combined comparative analysis for latency, throughput, payload size, and reliability. Data Communication Workflow.txt – JSON field format used for both PSK and DSEKP data exchange. Figures and Screenshots – Our_RealWorld_Setup.jpg, PSK_DATA_MATLAB_ANALYSIS.png, DSEKP_DATA_MATLAB_ANALYSIS.png, PSK-vs-DSEKP.png, secure_IOT-Edge_Communication_Flow.png. ⚙️ Experimental Environment Hardware: ESP32 (38-pin dev board, DHT11 sensor), Raspberry Pi 5 (16 GB RAM, Ubuntu 22.04 LTS). Software: Arduino IDE 2.2, Python 3.11, MATLAB R2023b, Eclipse Mosquitto 2.0 (Docker Compose). Dataset Size: ~6500 packets per protocol, sampled at 2 s intervals. 📊 Key Findings 27 % latency overhead (mean PSK = 283 ms → DSEKP = 360 ms) 10 % payload increase (HKDF metadata addition) 99.8 % reliability across sessions 🔄 Reproducibility Rebuild environment using Docker (docker-compose.yml inside SERVER-SIDE). Flash ESP32 sketches in CLIENT-SIDE. Run experiments and compare outputs with provided MATLAB analysis scripts. 🔒 License Creative Commons Attribution – NonCommercial 4.0 International (CC BY-NC 4.0) This record is restricted for peer review. Upon publication, the dataset will be made public with the same DOI.