Datasets:

hardware-fab
/

Chameleon

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 ---
 license: cc-by-4.0
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-Dataset on unprocessed real-world measurements specifically designed for the localization in side-channel analysis, made harder by hiding countermeasures.

 ---
 license: cc-by-4.0
+tags:
+- AES
+- RISC-V
+- Random-Delay
+- Dynamic-Frequency-Scaling
+- Chaffing
+- Morphing
+- Side-Channel-Analysis
+pretty_name: Chameleon
+size_categories:
+- 1K<n<10K
+configs:
+- config_name: DFS
+  data_files: "DFS/*.h5"
+- config_name: RD
+  data_files: "RD/*.h5"
+- config_name: MRP
+  data_files: "MRP/*.h5"
+- config_name: CHF
+  data_files: "CHF/*.h5"
 ---
+# Chameleon
+The `Chameleon` is a dataset designed for side-channel analysis of obfuscated power traces.
+It contains real-world power traces collected from a 32-bit RISC-V System-on-Chip
+implementing four hiding countermeasures: Dynamic Frequency Scaling (DFS),
+Random Delay (RD), Morphing (MRP), and Chaffing (CHF).
+Each side-channel trace includes multiple cryptographic operations
+interleaved with general-purpose applications.
+- **Curated by:** hardware-fab
+- **License:** Open Data Commons License [cc-by-4.0](https://huggingface.co/datasets/choosealicense/licenses/blob/main/markdown/cc-by-4.0.md)
+<div align="center">
+   <img src="https://github.com/hardware-fab/chameleon-dataset/blob/main/images/chameleon_logo.png?raw=true" alt="Chameleon Logo" width="150">
+</div>
+The dataset is designed to aid research in:
+- Segmentation methods (locate and isolate cryptographic operations)
+- Side-channel analysis methods (attacking devices with hiding countermeasures)
+## How to Download
+Full dataset:
+```python
+from datasets import load_dataset
+dataset = load_dataset("hardware-fab/Chameleon")
+```
+One sub-dataset of choice:
+```python
+from datasets import load_dataset
+sub_dataset = load_dataset("hardware-fab/Chameleon", '<sub_dataset>')
+```
+Replace `<sub_dataset>` with `DFS`, `RD`, `MRP`, or `CHF`.
+## Dataset Structure
+The dataset is divided per hiding countermeasure. Each file has the following structure:
+* **Data:** The data are power traces of 134,217,550 time samples. DFS, RD, MRP, and CHF datasets
+ contain 256, 512, 512, and 1024 data respectively. The traces capture the SoC execution of AES encryptions interleaved with general-purpose applications.
+* **Metadata:** The metadata are divided into three groups:
+  * **Ciphers:** This group contains the AES inputs:
+    * `key`: The secret key used for AES encryption.
+    * `plaintexts`: The plaintext used for the AES encryption.
+  * **Pinpoints:** This group contains the start and end time samples of each AES execution in each trace file.
+    * `start`: The starting sample of the AES encryption. It takes values ranging from 0 to 134,217,550.
+    * `end`: The ending sample of the AES encryption. It takes values ranging from 0 to 134,217,550.
+  * **Frequencies:** This group provides labels for each power trace, indicating the frequency changes during the measurement. _Notably, this metadata is only available for the DFS dataset_.Each metadata has two fields:
+    * `samples`: This field denotes the time sample at which a frequency change happens, with integer values ranging from 0 to 134,217,550.
+    * `frequencies`: This field specifies the new operating frequency starting from the corresponding sample. It can take floating values from 5MHz to 100MHz.
+### Dataset Format
+The dataset is divided into four sub-datasets, one for each hiding countermeasure,
+stored in different folders. To alleviate the size of the individual files,
+we partitioned each sub-dataset into 16 files based on the cryptographic key.
+Keys are 16-byte arrays, we vary only the first byte in each trace,
+keeping the remaining 15 fixed.
+| Chunk          | First key byte values | Disk size (GB) | # Data  |
+|----------------|----------------|----------------|----------------|
+| dfs_chunk_1.h5  | [0x00-0x0f] | 4.3  | 16 |
+| dfs_chunk_2.h5  | [0x10-0x0f] | 4.3  | 16 |
+| dfs_chunk_3.h5  | [0x20-0x2f] | 4.3  | 16 |
+| dfs_chunk_4.h5  | [0x30-0x3f] | 4.3  | 16 |
+| dfs_chunk_5.h5  | [0x40-0x4f] | 4.3  | 16 |
+| dfs_chunk_6.h5  | [0x50-0x5f] | 4.3  | 16 |
+| dfs_chunk_7.h5  | [0x60-0x6f] | 4.3  | 16 |
+| dfs_chunk_8.h5  | [0x70-0x7f] | 4.3  | 16 |
+| dfs_chunk_9.h5  | [0x80-0x8f] | 4.3  | 16 |
+| dfs_chunk_10.h5 | [0x90-0x9f] | 4.3  | 16 |
+| dfs_chunk_11.h5 | [0xa0-0xaf] | 4.3  | 16 |
+| dfs_chunk_12.h5 | [0xb0-0xbf] | 4.3  | 16 |
+| dfs_chunk_13.h5 | [0xc0-0xcf] | 4.3  | 16 |
+| dfs_chunk_14.h5 | [0xd0-0xdf] | 4.3  | 16 |
+| dfs_chunk_15.h5 | [0xe0-0xef] | 4.3  | 16 |
+| dfs_chunk_16.h5 | [0xf0-0xff] | 4.3  | 16 |
+| rd_chunk_1.h5   | [0x00-0x0f] | 8.6  | 32 |
+| rd_chunk_2.h5   | [0x10-0x0f] | 8.6  | 32 |
+| rd_chunk_3.h5   | [0x20-0x2f] | 8.6  | 32 |
+| rd_chunk_4.h5   | [0x30-0x3f] | 8.6  | 32 |
+| rd_chunk_5.h5   | [0x40-0x4f] | 8.6  | 32 |
+| rd_chunk_6.h5   | [0x50-0x5f] | 8.6  | 32 |
+| rd_chunk_7.h5   | [0x60-0x6f] | 8.6  | 32 |
+| rd_chunk_8.h5   | [0x70-0x7f] | 8.6  | 32 |
+| rd_chunk_9.h5   | [0x80-0x8f] | 8.6  | 32 |
+| rd_chunk_10.h5  | [0x90-0x9f] | 8.6  | 32 |
+| rd_chunk_11.h5  | [0xa0-0xaf] | 8.6  | 32 |
+| rd_chunk_12.h5  | [0xb0-0xbf] | 8.6  | 32 |
+| rd_chunk_13.h5  | [0xc0-0xcf] | 8.6  | 32 |
+| rd_chunk_14.h5  | [0xd0-0xdf] | 8.6  | 32 |
+| rd_chunk_15.h5  | [0xe0-0xef] | 8.6  | 32 |
+| rd_chunk_16.h5  | [0xf0-0xff] | 8.6  | 32 |
+| mrp_chunk_1.h5  | [0x00-0x0f] | 8.6  | 32 |
+| mrp_chunk_2.h5  | [0x10-0x0f] | 8.6  | 32 |
+| mrp_chunk_3.h5  | [0x20-0x2f] | 8.6  | 32 |
+| mrp_chunk_4.h5  | [0x30-0x3f] | 8.6  | 32 |
+| mrp_chunk_5.h5  | [0x40-0x4f] | 8.6  | 32 |
+| mrp_chunk_6.h5  | [0x50-0x5f] | 8.6  | 32 |
+| mrp_chunk_7.h5  | [0x60-0x6f] | 8.6  | 32 |
+| mrp_chunk_8.h5  | [0x70-0x7f] | 8.6  | 32 |
+| mrp_chunk_9.h5  | [0x80-0x8f] | 8.6  | 32 |
+| mrp_chunk_10.h5 | [0x90-0x9f] | 8.6  | 32 |
+| mrp_chunk_11.h5 | [0xa0-0xaf] | 8.6  | 32 |
+| mrp_chunk_12.h5 | [0xb0-0xbf] | 8.6  | 32 |
+| mrp_chunk_13.h5 | [0xc0-0xcf] | 8.6  | 32 |
+| mrp_chunk_14.h5 | [0xd0-0xdf] | 8.6  | 32 |
+| mrp_chunk_15.h5 | [0xe0-0xef] | 8.6  | 32 |
+| mrp_chunk_16.h5 | [0xf0-0xff] | 8.6  | 32 |
+| chf_chunk_1.h5  | [0x00-0x0f] | 17.2 | 64 |
+| chf_chunk_2.h5  | [0x10-0x0f] | 17.2 | 64 |
+| chf_chunk_3.h5  | [0x20-0x2f] | 17.2 | 64 |
+| chf_chunk_4.h5  | [0x30-0x3f] | 17.2 | 64 |
+| chf_chunk_5.h5  | [0x40-0x4f] | 17.2 | 64 |
+| chf_chunk_6.h5  | [0x50-0x5f] | 17.2 | 64 |
+| chf_chunk_7.h5  | [0x60-0x6f] | 17.2 | 64 |
+| chf_chunk_8.h5  | [0x70-0x7f] | 17.2 | 64 |
+| chf_chunk_9.h5  | [0x80-0x8f] | 17.2 | 64 |
+| chf_chunk_10.h5 | [0x90-0x9f] | 17.2 | 64 |
+| chf_chunk_11.h5 | [0xa0-0xaf] | 17.2 | 64 |
+| chf_chunk_12.h5 | [0xb0-0xbf] | 17.2 | 64 |
+| chf_chunk_13.h5 | [0xc0-0xcf] | 17.2 | 64 |
+| chf_chunk_14.h5 | [0xd0-0xdf] | 17.2 | 64 |
+| chf_chunk_15.h5 | [0xe0-0xef] | 17.2 | 64 |
+| chf_chunk_16.h5 | [0xf0-0xff] | 17.2 | 64 |
+Following the structure of the dataset, below are HDF5 fields used and their atomic type:
+```
+.
+├── data
+│    └── traces
+│       ├── trace_0 [int16]
+│       ├── ...
+│       └── trace_n [int16]
+└── metadata
+    ├── ciphers
+    │   ├── ciphers_0
+    │   │   ├── key [('k', uint8, (16,))]
+    │   │   └── plaintexts [('p', uint8, (16,))]
+    │   ├── ...
+    │   └── ciphers_n
+    │       ├── key [('k', uint8, (16,))]
+    │       └── plaintexts [('p', uint8, (16,))]
+    ├── pinpoints
+    │   ├── pinpoints_0 [('start', int32), ('end', int32)]
+    │   ├── ...
+    │   └── pinpoints_n [('start', int32), ('end', int32)]
+    └── frequencies
+        ├── frequencies_0  [('sample', int32), ('frequency', float32)]
+        ├── ...
+        └── frequencies_n  [('sample', int32), ('frequency', float32)]
+```
+## Dataset Creation
+Existing datasets for side-channel analysis lack real-world complexity.
+Chameleon addresses this by providing the first dataset of:
+- **Real-world hiding methods**: Traces are collected from a real system implementing four actual obfuscation countermeasures (DFS, RD, MRP, CHF).
+- **Segmentable cryptographic operations**: Chameleon includes multiple operations interleaved with real-world applications,
+  mimicking real-world use and necessitating segmentation techniques for attack.
+### Data Collection
+The data are collected from a real-world hardware-software infrastructure.
+The setup comprises a host PC,
+a [Picoscope 5244d](https://www.picotech.com/download/datasheets/picoscope-5000d-series-data-sheet.pdf)
+digital sampling oscilloscope (DSO), and
+a [NewAE CW305](https://rtfm.newae.com/Targets/CW305%20Artix%20FPGA/)
+board which hosts an [AMD Artix-7 FPGA](https://docs.amd.com/v/u/en-US/ds180_7Series_Overview).
+The board is specifically designed to facilitate the deployment
+of digital designs targeting FPGAs and studying their side-channel behavior.
+The sampling rate of the DSO is set to 125Msample/s
+with a resolution of 12 bits for the entire dataset.
+The FPGA implements a system-on-chip consisting of a 1.5Mps UART
+interface to communicate with the host, a computing platform
+to execute the user applications, and a pinpointing unit
+to record the beginning and end time sample for each cryptographic operation in the traces.
+The computing platform implements an in-order 32-bit RISC-V CPU
+that has been modified to implement the analyzed hiding methods. In particular,
+we implement random delay and dynamic frequency scaling in hardware,
+while morphing and chaffing are software-implemented. Notably,
+the CPU is clocked at 50MHz for all acquisition campaigns,
+except for the DFS one, for which the DFS actuator
+is instructed to change the operating frequency of
+the computing platform randomly at its maximum speed.
+As the cryptographic operation of choice, we selected
+the [OpenSSL AES implementation](https://github.com/openssl/openssl),
+representing the standard for symmetric cryptography.
+## Social Impact of Dataset
+Chameleon has been developed to enhance side-channel security.
+Notably, the side-channel analysis represents a standard procedure
+for evaluating novel countermeasures. Indeed,
+the [NIST FIPS-140v3](https://doi.org/10.6028/NIST.FIPS.140-3)
+standard enforces side-channel security as a mandatory step
+in the security validation of any novel software- and
+hardware-implemented cryptographic device. To this end,
+Chameleon is a valuable asset in strengthening real-world security
+by enabling researchers to identify and address potential
+weaknesses in cryptographic implementations.
+By promoting the creation of robust countermeasures,
+this dataset ultimately contributes to a more secure digital world.
+As creating a high-quality training dataset is a fundamental requirement, the quality of Chameleon
+sits on the time-consuming acquisition process that requires a clean-room acquisition setup and
+system-on-chip. Without considering the design time to obtain the implementation of the computing
+platform and the working acquisition setup, the time required by the acquisition procedure exceeded
+58 hours.
+<!-- ## Citation -->
+<!-- **BibTeX:** -->
+<!-- **APA:** -->
+## Note
+This repository is protected by copyright and licensed under the
+Open Data Commons License [cc-by-4.0](https://huggingface.co/datasets/choosealicense/licenses/blob/main/markdown/cc-by-4.0.md) file.
+© 2024 hardware-fab