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metadata
dataset_info:
  features:
    - name: sender
      dtype: large_string
    - name: sender_domain
      dtype: large_string
    - name: receiver
      dtype: large_string
    - name: receiver_domain
      dtype: large_string
    - name: date
      dtype: large_string
    - name: subject
      dtype: large_string
    - name: content_types
      dtype: large_string
    - name: body
      dtype: large_string
    - name: urls
      dtype: large_string
    - name: url_count
      dtype: float64
    - name: url_length_max
      dtype: float64
    - name: url_length_avg
      dtype: float64
    - name: url_subdom_max
      dtype: float64
    - name: url_subdom_avg
      dtype: float64
    - name: attachment_count
      dtype: float64
    - name: has_attachments
      dtype: bool
    - name: attachment_types
      dtype: large_string
    - name: language
      dtype: large_string
    - name: source
      dtype: large_string
    - name: label
      dtype: float64
  splits:
    - name: train
      num_bytes: 201554227
      num_examples: 108685
  download_size: 82741534
  dataset_size: 201554227
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
license: cc-by-4.0
tags:
  - email
  - phishing
pretty_name: 'MeAJOR: Merged email Assets from Joint Open-source Repositories'

Dataset Card for MeAJOR: Merged email Assets from Joint Open-source Repositories

The MeAJOR dataset was created with multi-source legitimate emails and malicious emails from different attack campaigns to enable a more reliable phishing detection. MeAJOR provides a total of 108685 data samples, in preprocessed format with engineered features suitable for the training, validation, and testing of ML and DL models.

Dataset Details

The dataset was created at GECAD, ISEP, Polytechnic of Porto. It contains data collected from publicly available spam email and phishing email datasets:

TREC-05 TREC-06 TREC-07 Nazario Phishing Corpus Nigerian Fraud The dataset contains the email messages anonymized, source dataset and label (0 = benign; 1 = phishing). It also contains several extracted features suitable for email phishing attack detection. The email messages are anonymized using Entity Removal, with tokens replacing them, enclosed between square brackets. The tokens are as follow: [PGP], [EMOJI], [SYMBOL], [NAME], [USERNAME], [INITIALS], [EMAIL_ADDRESS], [PHONE_NUMBER], [ADDRESS], [ORGANIZATION], [URL], [IP_ADDRESS], [FILE_PATH], [FILE_NAME], [FILE], [DATE], [TIME], [FINANCIAL_INFO], [PRODUCT], [REFERENCE_NUMBER].

  • License: CC-BY-4.0

Dataset Sources [optional]