Detection of malicious webmail attachments based on propagation patterns-Reference-Cited by-同舟云学术

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Detection of malicious webmail attachments based on propagation patterns

Published:2018-02 Issue: Volume:141 Page:67-79
ISSN:0950-7051
Container-title:Knowledge-Based Systems
language:en
Short-container-title:Knowledge-Based Systems

Author:

Cohen Yehonatan,Hendler Danny,Rubin Amir

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Management Information Systems,Software

Reference56 articles.

1. Hunting for metamorphic Javascript malware;Musale;J. Comput. Virol. Hacking Tech.,2015

2. Malware obfuscation techniques: a brief survey;You,2010

3. Email Statistics Report;The Radicati Group,2016

4. Internet Security Threat Report;Symantec Corporation,2015

5. Security Intelligence Report;Microsoft Corporation,2015

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1. A Study on Machine Learning and Deep Learning Techniques for Identifying Malicious Web Content;SN Computer Science;2024-08-16

2. Classifying spam emails using agglomerative hierarchical clustering and a topic-based approach;Applied Soft Computing;2023-05

3. Improving malicious email detection through novel designated deep-learning architectures utilizing entire email;Neural Networks;2023-01

4. Measuring and fostering diversity in Affective Computing research;IEEE Transactions on Affective Computing;2023

5. Research on the Propagation Model and Prevention Strategy of Industrial Internet Worm Based on Coupled P2P Network;2022 10th International Conference on Information Systems and Computing Technology (ISCTech);2022-12

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