188 lines
5.4 KiB
Python
188 lines
5.4 KiB
Python
# File: entropy.py
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# Copyright (C) 2026 Erick Ahmed
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# SPDX-License-Identifier: AGPL-3.0-or-later
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import argparse
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from pathlib import Path
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import numpy as np
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import pandas as pd
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import plotly.graph_objects as go
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from utils.extractor import load_data
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from utils.extractor import to_int
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def _format_can_id(x):
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"""Safely cleans CAN ID strings without altering their length or value."""
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if pd.isna(x):
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return "UNKNOWN"
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s = str(x).strip()
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if not s:
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return "UNKNOWN"
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if s.lower().startswith('0x'):
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s = s[2:]
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return s.upper()
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def calculate_byte_entropy(df: pd.DataFrame) -> pd.DataFrame:
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"""Calculates Shannon entropy per byte position for each identifier."""
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byte_cols = [f"b{i}" for i in range(8)]
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available_cols = [col for col in byte_cols if col in df.columns]
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if not available_cols:
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raise ValueError("No byte columns (b0-b7) found in the DataFrame")
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can_id_col = 'ID' if 'ID' in df.columns else 'Identifier'
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identifiers = df[can_id_col].apply(_format_can_id)
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df_bytes = df[available_cols].copy()
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for col in available_cols:
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df_bytes[col] = df_bytes[col].apply(to_int)
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def entropy(s: pd.Series) -> float:
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s = s.dropna()
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if s.empty:
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return 0.0
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p = s.value_counts(normalize=True)
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return -np.sum(p * np.log2(p))
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result = df_bytes.groupby(identifiers)[available_cols].agg(entropy)
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result.index.name = 'Identifier'
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return result
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def plot_entropy_heatmap(entropy_df: pd.DataFrame, title: str) -> go.Figure:
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"""Generates an interactive heatmap of byte-level Shannon entropy."""
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x = entropy_df.columns.tolist()
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y = entropy_df.index.tolist()
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z = entropy_df.values
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fig = go.Figure(
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data=go.Heatmap(
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z=z,
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x=x,
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y=y,
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colorscale=[
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[0.0, "#ffffff"],
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[0.15, "#fff7ec"],
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[0.35, "#fee8c8"],
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[0.55, "#fdd49e"],
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[0.75, "#fdbb84"],
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[1.0, "#ef6548"],
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],
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xgap=3,
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ygap=3,
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text=np.round(z, 2),
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texttemplate="%{text}",
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textfont={
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"size": 11,
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"color": "#2a2a2a",
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"family": "Segoe UI, Arial, sans-serif",
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},
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hoverongaps=False,
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hovertemplate=(
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"<b>%{y}</b><br>"
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"Byte %{x}: %{z:.2f} bits<extra></extra>"
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),
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colorbar=dict(
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title=dict(
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text="Entropy (bits)",
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side="top",
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font=dict(size=13, color="#1a1a1a"),
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),
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orientation="h",
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thickness=15,
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len=0.35,
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x=1.0,
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xanchor="right",
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y=1.02,
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yanchor="bottom",
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tickfont=dict(size=11, color="#2a2a2a"),
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tickformat=".1f",
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outlinewidth=0.5,
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outlinecolor="#cccccc",
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),
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)
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)
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fig.update_layout(
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title=dict(
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text=title,
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font=dict(size=20, color="#1a1a1a"),
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x=0.5,
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xanchor="center",
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pad=dict(b=20),
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),
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height=max(600, len(y) * 28 + 150),
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autosize=True,
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template="plotly_white",
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xaxis=dict(
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title=dict(text="Byte Position", font=dict(size=13, color="#1a1a1a")),
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side="top",
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dtick=1,
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showgrid=False,
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linecolor="#bdbdbd",
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tickfont=dict(size=12, color="#2a2a2a"),
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ticks="outside",
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ticklen=4,
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tickcolor="#cccccc",
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),
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yaxis=dict(
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title=dict(text="PGN or CAN ID", font=dict(size=13, color="#1a1a1a")),
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autorange="reversed",
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showgrid=False,
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linecolor="#bdbdbd",
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tickfont=dict(size=12, color="#2a2a2a"),
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ticks="outside",
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ticklen=4,
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tickcolor="#cccccc",
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automargin=True,
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),
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font=dict(family="Segoe UI, Arial, sans-serif", size=12, color="#2a2a2a"),
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hoverlabel=dict(
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bgcolor="white",
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font_size=13,
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font_family="Segoe UI",
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bordercolor="#cccccc",
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),
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margin=dict(l=200, r=40, t=120, b=60),
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)
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return fig
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(
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description="Analyze CAN bus byte-level entropy"
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)
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parser.add_argument(
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"input", type=Path, help="Path to the input CAN log file"
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)
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parser.add_argument(
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"output",
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type=Path,
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nargs="?",
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default=Path("entropy_report.html"),
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help="Path to the output HTML report",
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)
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parser.add_argument(
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"title",
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nargs="?",
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default="CAN Bus Byte-Level Entropy",
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help="Title for the HTML report",
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)
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args = parser.parse_args()
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df = load_data(args.input)
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entropy_df = calculate_byte_entropy(df)
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fig = plot_entropy_heatmap(entropy_df, title=args.title)
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config = {
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"responsive": True,
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"displaylogo": False,
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"scrollZoom": True,
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"modeBarButtonsToAdd": ["toggleSpikelines"],
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"toImageButtonOptions": {"format": "png", "scale": 2},
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}
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fig.write_html(str(args.output), include_plotlyjs="cdn", config=config)
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