Corpus ID: 233289841

Holmes: An Efficient and Lightweight Semantic Based Anomalous Email Detector

@article{Wu2021HolmesAE,
  title={Holmes: An Efficient and Lightweight Semantic Based Anomalous Email Detector},
  author={Peilun Wu and Shiyi Yang and Hui Guo},
  journal={ArXiv},
  year={2021},
  volume={abs/2104.08044}
}
Email threat is a serious issue for enterprise security, which can be in various malicious forms, such as phishing, fraud, blackmail and malvertisement. Traditional antispam gateway maintains a greylist to filter out unexpected emails based on suspicious vocabularies present in the email’s subject and contents. However, this type of signature-based approach cannot effectively discover novel and unknown suspicious emails that utilize various up-to-date hot topics, such as COVID-19 and US… Expand

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