Efficient Clustering of Emails Into Spam and Ham: The Foundational Study of a Comprehensive Unsupervised Framework

Efficient Clustering of Emails Into Spam and Ham: The Foundational Study of a Comprehensive Unsupervised Framework

The spread and adoption of spam emails in malicious activities like information and identity theft, malware propagation, monetary and reputational damage etc. are on the rise with increased effectiveness and diversification. Without doubt these criminal acts endanger the privacy of many users and bu...

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Bibliographic Details
Main Authors: Asif Karim, Sami Azam, Bharanidharan Shanmugam, Krishnan Kannoorpatti
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Machine learning
phishing attack
spam detection
spam email
spam filtering
clustering
Online Access:https://ieeexplore.ieee.org/document/9169622/

Internet

https://ieeexplore.ieee.org/document/9169622/

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