File size: 3,302 Bytes
4b0fa34 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 |
---
license: cc-by-nc-4.0
task_categories:
- text-classification
- image-classification
- multimodal
tags:
- web-security
- phishing-detection
- html-analysis
- screenshot
- manually-verified
dataset_info:
features:
- name: url
dtype: string
description: Website URL and folder name for resource access
- name: html_content
dtype: string
description: "Path to HTML file (format: {url}/page.html)"
- name: screenshot_content
dtype: image
description: "Path to screenshot image (format: {url}/screenshot.png)"
- name: label
dtype: string
description: Classification label from metadata.txt (phishing/legitimate)
splits:
- name: train
num_bytes: 1024000000
num_examples: 1000
configs:
- config_name: default
data_files:
- split: train
path: data/dataset.csv
---
# Web Content Classification Dataset with HTML and Screenshots
## Dataset
Description: This dataset contains 1,000 carefully curated examples of web content designed for phishing detection classification tasks. Each example consists of a website URL along with its complete HTML content, a visual screenshot, and a manually verified classification label.
Important Note: This entire dataset was meticulously created through manual processes. Each website was individually visited, analyzed, and verified to ensure the highest quality and accuracy of labels.
## Dataset Structure
The dataset is organized with a main CSV file that references all resources using a consistent folder structure:
### CSV Columns:
- url: Website URL and folder name for resource access
- html_content: Path to HTML file (`{url}/page.html`)
- screenshot_content: Path to screenshot image (`{url}/screenshot.png`)
- label: Classification label (phishing/legitimate)
### Directory Structure:
dataset:
files:
- dataset.csv
folders:
- name: example-domain-1.com
files:
- page.html
- screenshot.png
- metadata.txt
- name: example-domain-2.com
files:
- page.html
- screenshot.png
- metadata.txt
## File Reference System
The dataset uses a consistent referencing system where each URL serves as both the website address and folder name:
- HTML Content: "{url}/page.html (e.g., `example.com/page.html`)"
- Screenshot: "{url}/screenshot.png (e.g., `example.com/screenshot.png`) "
- Label: Value contained in `{url}/metadata.txt`
## Collection Methodology
### Manual Curation Process
This dataset was created through an extensive manual verification process:
1. Individual Website Visits: Each of the 1,000 websites was personally visited and analyzed
2. Manual Verification: Every classification label was manually assigned after careful examination
3. Quality Control: Each entry was individually checked for accuracy and completeness
4. Content Capture: HTML and screenshots were captured while ensuring proper rendering
### Data Points Collected:
data_points:
URL: "The exact folder name and web address"
HTML content: "Full source code saved as {url}/page.html"
Visual representation: "High-quality screenshot saved as `{url}/screenshot.png`"
Classification label: "Value stored in `{url}/metadata.txt` (verified as phishing/legitimate)"
|