POST: Email Archival, Processing and Flagging Stack for Incident Responders
Fuente:
arXiv
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866909236536016896 |
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| author | Fairbanks, Jeffrey |
| author_facet | Fairbanks, Jeffrey |
| contents | Phishing is one of the main points of compromise, with email security and awareness being estimated at \$50-100B in 2022. There is great need for email forensics capability to quickly search for malicious content. A novel solution POST is proposed. POST is an API driven serverless email archival, processing, and flagging workflow for both large and small organizations that collects and parses all email, flags emails using state of the art Natural Language Processing and Machine Learning, allows full email searching on every aspect of an email, and provides a cost savings of up to 68.6%. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_01433 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | POST: Email Archival, Processing and Flagging Stack for Incident Responders Fairbanks, Jeffrey Cryptography and Security Information Retrieval Machine Learning Phishing is one of the main points of compromise, with email security and awareness being estimated at \$50-100B in 2022. There is great need for email forensics capability to quickly search for malicious content. A novel solution POST is proposed. POST is an API driven serverless email archival, processing, and flagging workflow for both large and small organizations that collects and parses all email, flags emails using state of the art Natural Language Processing and Machine Learning, allows full email searching on every aspect of an email, and provides a cost savings of up to 68.6%. |
| title | POST: Email Archival, Processing and Flagging Stack for Incident Responders |
| topic | Cryptography and Security Information Retrieval Machine Learning |
| url | https://arxiv.org/abs/2407.01433 |