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README.md

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+# SC2026: Screaming Channel 2026 Dataset
+
+SC2026 is a large-scale public dataset for **Far-Field Electromagnetic Side-Channel Attacks (FEM-SCAs)**, also known as **Screaming Channel Attacks**.  
+The dataset is designed to support **systematic, realistic, and reproducible evaluation** of long-range EM side-channel attacks under diverse conditions.
+
+It contains far-field EM traces captured from **Bluetooth-enabled IoT devices** executing multiple cryptographic algorithms, across **different distances and physical barriers**.
+
+📌 This dataset accompanies the paper:
+
+> **A Systematic Far Field EM Side-Channel Evaluation and Introduction of SC2026 Dataset**  
+> *Not yet published*
+
+---
+
+## 🔍 Key Features
+
+- 📡 **Far-field EM leakage** (wireless, over-the-air)
+- 🔐 **Multiple cryptographic algorithms**
+  - AES
+  - SM4
+  - CRYSTALS-Kyber
+- 📏 **Multiple attack distances**
+  - 0 m (coaxial cable baseline)
+  - 3 m / 6 m / 9 m / 12 m / 15 m
+  - 30 m (open-field scenario)
+- 🧱 **Physical barriers**
+  - Plastic
+  - Wood
+  - Metal
+- 🧠 **Supports both classical and deep-learning SCAs**
+  - CPA, Template Attack
+  - CNN / MLP / Transformer / Domain Adaptation models
+- 📂 **NumPy format (.npy)** for efficient loading and training
+
+---
+
+## 📦 Dataset Structure
+
+The SC2026 dataset is divided into **two main subsets**:
+
+### 1️⃣ Profiling Set (High-Quality Reference)
+
+Used for building leakage models.
+
+- Capture method: **Coaxial cable**
+- Purpose: Profiling / training
+- Traces per algorithm: **40,000**
+- Each trace:
+  - Averaged over **100 repeated measurements**
+  - Plus a **corresponding single-trace (non-averaged) version**
+- Algorithms & labels:
+  - **AES / SM4**: plaintext & key
+  - **Kyber**: message bit
+
+📌 This design enables:
+- Profiling attacks
+- Transfer learning
+- Domain adaptation
+- Denoising and robustness studies
+
+---
+
+### 2️⃣ Testing Set (Realistic Attack Scenarios)
+
+Used for evaluating attack performance under realistic conditions.
+
+- Capture method: **Over-the-air (far-field EM)**
+- Traces per scenario: **5,000**
+- No averaging, no repetition
+- Covers:
+  - Different distances
+  - Different environments
+  - Different physical barriers
+
+Each scenario is stored as an independent `.npy` file for clarity and reproducibility.
+
+---
+
+## 📁 Example Directory Layout
+
+```text
+SC2026/
+├── profiling/
+│   ├── AES/
+│   │   ├── traces_avg.npy
+│   │   ├── traces_single.npy
+│   │   ├── plaintext.npy
+│   │   └── key.npy
+│   ├── SM4/
+│   └── Kyber/
+│
+├── testing/
+│   ├── distance_3m/
+│   │   ├── AES.npy
+│   │   ├── SM4.npy
+│   │   └── Kyber.npy
+│   ├── distance_15m/
+│   ├── distance_30m/
+│   ├── barrier_plastic/
+│   ├── barrier_wood/
+│   └── barrier_metal/
+│
+└── README.md
+```
+---
+
+## How to Download
+Full dataset:  
+```python 
+from huggingface_hub import snapshot_download
+snapshot_download(repo_id="SCA-HNUST/SC2026", repo_type="dataset", local_dir="<download_path>")
+```
+
+One sub-dataset of choice:
+```python 
+from huggingface_hub import snapshot_download
+snapshot_download(repo_id="SCA-HNUST/SC2026",repo_type="dataset",local_dir="<download_path>",allow_patterns="<sub_dataset>/*")
+```
+Replace `<sub_dataset>` with 'AES','SM4','CRYSTALS-Kyber'.
+
+---
+
+
+## 🧪 Experimental Setup Overview
+
+- **Target device**: Nordic nRF52 DK (nRF52832)
+- **Radio**: Bluetooth Low Energy (2.4 GHz)
+
+**Receiver**:
+- Ettus N210 USRP
+- SBX RF daughterboard
+- 24 dBi directional antenna
+
+**Signal acquisition**:
+- Sampling rate: 5 MHz
+- Center frequency: 2.272 GHz
+
+**Environments**:
+- Indoor: office corridor
+- Outdoor: open field
+
+Both indoor (office corridor) and outdoor (open field) environments are included.
+
+---
+## 📜 Citation
+
+If you use SC2026 in your research, please cite:
+
+```bibtex
+@article{wang2025sc2026,
+  title={A Systematic Far Field EM Side-Channel Evaluation and Introduction of SC2026 Dataset},
+  author={Wang, Huanyu and Wang, Xiaoxia and Ge, Kaiqiang and Yao, Jinjie and Tan, Xinyan and Wang, Junnian},
+  journal={IEEE Transactions on Information Forensics and Security},
+  year={2025}
+}
+```
+---
+
+## 🤝 Contact
+
+For questions, feedback, or collaboration, please contact:
+
+Huanyu Wang 
+School of Computer Science and Engineering  
+Hunan University of Science and Technology