SeFACED: Semantic-Based Forensic Analysis and Classification of E-Mail Data Using Deep Learning-Reference-Cited by-同舟云学术

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SeFACED: Semantic-Based Forensic Analysis and Classification of E-Mail Data Using Deep Learning

Published:2021 Issue: Volume:9 Page:98398-98411
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Hina Maryam,Ali Mohsin,Javed Abdul Rehman^ORCID,Ghabban Fahad,Khan Liaqat Ali,Jalil Zunera^ORCID

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/6287639/9312710/09477611.pdf?arnumber=9477611

Cited by 34 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Forensic analysis of web browsers lifecycle: A case study;Journal of Information Security and Applications;2024-09

2. A robust approach to authorship verification using siamese deep learning: application in phishing email detection;International Journal of Speech Technology;2024-06

3. Enhancing cold storage infrastructure efficiency through IoT, image processing and solar panel;AIP Conference Proceedings;2024

4. OntoFoCE and ObE Forensics. Email-traceability supporting tools for digital forensics;JUCS - Journal of Universal Computer Science;2023-12-28

5. Multi-level Data Integrity Model with Dual Immutable Digital Key Based Forensic Analysis in IoT Network;SN Computer Science;2023-12-12

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