Upload ASCAD (Unified TileDB Group)

.gitattributes

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README.md

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+---
+license: mit
+task_categories:
+- other
+pretty_name: tile-ascad-fk
+tags:
+- side-channel-analysis
+- dlsca
+- power-traces
+- aes
+- ascad
+- cryptography
+- tiledb
+num_traces: 60000
+trace_length: 100000
+row_chunks: 600
+col_chunks: 100
+chunk_size: 100
+cols_per_chunk: 1000
+tiles: 60000
+ascad_variant: unknown
+source: ascad_v1_full
+---
+
+# tile-ascad-fk
+
+## Dataset Description
+
+ASCAD v1 Full (raw traces) converted to a unified **TileDB Group**. 
+Both traces and metadata are stored as TileDB arrays within the same logical group.
+
+### Dataset Details
+- **Format**: TileDB Group
+- **Structure**:
+  - `traces`: 2D Dense Array (float/int)
+  - `metadata`: 1D Array (plaintext, key, etc. stored as binary attributes)
+- Number of traces: 60,000
+- Trace length: 100,000 samples per trace
+
+### Files
+The dataset is uploaded as a folder structure representing the TileDB Group:
+- `traces/` 
+- `metadata/`
+- `__tiledb_group.tdb`
+
+## Usage
+
+Use `tiledb` to open the group or individual arrays.
+
+```python
+import tiledb
+import numpy as np
+
+# Download/Path to dataset folder
+group_uri = "."  # or path to downloaded folder
+
+# 1. Open the Group
+with tiledb.Group(group_uri, mode='r') as G:
+    print("Group members:", [m.name for m in G])
+
+# 2. Read Traces (Lazy slicing)
+with tiledb.DenseArray(f"{group_uri}/traces", mode='r') as A:
+    # Read first 10 traces
+    traces = A[0:10, :]
+    print("Traces shape:", traces["trace"].shape)
+
+# 3. Read Metadata
+with tiledb.open(f"{group_uri}/metadata", mode='r') as meta:
+    # Read metadata for first 5 traces
+    # Returns a dictionary of numpy arrays (bytes)
+    data = meta[0:5] 
+    
+    # Convert bytes back to numpy arrays if needed
+    plaintext_0 = np.frombuffer(data["plaintext"][0], dtype=np.uint8)
+    print("Plaintext #0:", plaintext_0)
+
+@dataset{ascad-dlsca-tiledb,
+  title={ASCAD v1 Full (Unified TileDB)},
+  author={DLSCA Platform},
+  year={2026},
+  publisher={HuggingFace},
+  url={[https://huggingface.co/datasets/](https://huggingface.co/datasets/){repo_id}}
+}

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