EdgeSec-Benchmark: IoT Security Resilience Dataset (ESP32, Raspberry Pi 5, Hardware-AES)
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https://zenodo.org/doi/10.5281/zenodo.18470802
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资源简介:
Experimental Dataset: Hardware-Accelerated Security in Edge IoT
This repository contains the complete telemetry and performance logs from a longitudinal experimental campaign evaluating the resilience of ESP32-based secure edge nodes communicating with a Raspberry Pi 5 Gateway. The data was collected to validate the performance of hardware-accelerated AES-GCM encryption under conditions of signal degradation (-88 dBm), network congestion (Bufferbloat), and power cycling.
📄 ASSOCIATED MANUSCRIPT
This dataset supports the findings presented in the research article:
"Benchmarking Hardware-Accelerated Security in Edge IoT: Impact of Signal Degradation and Network Congestion"
📂 DATASET STRUCTURE
EdgeSec_Benchmark_Dataset/
│
├── 01_Raw_Data/ (Original Server Logs - Raspberry Pi 5)
│ ├── Day-1/
│ │ ├── Baseline_Server_Day-1.csv
│ │ ├── Noise_Server_Day-1.csv
│ │ ├── Distance_Server_Day-1.csv
│ │ ├── Stress_Server_Day-1.csv
│ ├── Day-2/ ...
│ ├── Day-3/ ...
│ └── Client_Serial_Logs/ (Forensic Boot Logs - ESP32)
│ └── Stress_Client_DayX.txt
│
├── 02_Processed_Data/ (Cleaned & Merged)
│ ├── Total_Baseline.csv
│ ├── Total_Noise.csv
│ ├── Total_Distance.csv
│ └── Total_Stress.csv
│
├── 03_Analysis_Code/ (Reproducibility)
│ ├── EdgeSec_Reproducibility_Analysis.ipynb
│ └── extract_scientific_datapoints.py
│
└── README.txt
📊 COLUMN DEFINITIONS
seq: Sequence ID for calculating Packet Loss.
latency_ms: End-to-End Latency (Server_Rx - Client_Tx).
rssi: WiFi Signal Strength (dBm).
crypto_time_us: Encryption overhead (microseconds).
heap_free: Available memory (Bytes).
throughput: Bandwidth usage (Bytes/sec).
⚠️ DATA NOTE (NTP Exclusions)
While the Raw Data contains 30,953 packets, 322 packets (1.04%) were generated prior to client-side NTP synchronization. These were analytically excluded from the Processed Data to preserve precise end-to-end latency calculations, resulting in exactly 30,631 valid data points.
🛠 USAGE & REPRODUCIBILITY
The included Jupyter Notebook (EdgeSec_Reproducibility_Analysis.ipynb) and Python extraction script contain the logic required to process these CSVs and reproduce all statistical figures and Kruskal-Wallis H-tests found in the associated research manuscript.
Required Environment: Python 3.x (Tested on 3.14.0). To avoid Kernel execution errors (WinError 2), please ensure the following dependencies are installed in your virtual environment before running the notebook:
pandas>=2.0.0
numpy>=1.24.0
scipy>=1.10.0
seaborn>=0.12.0
matplotlib>=3.7.0
jupyter>=1.0.0
提供机构:
Zenodo
创建时间:
2026-02-03



