A Hybrid Deep Learning Approach for Advanced Persistent Threat Attack Detection-Reference-Cited by-同舟云学术

A Hybrid Deep Learning Approach for Advanced Persistent Threat Attack Detection

Published:2021-12-15 Issue: Volume: Page:
ISSN:
Container-title:The 5th International Conference on Future Networks & Distributed Systems
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Author:

Alrehaili Meaad¹,Alshamrani Adel¹,Eshmawi Ala¹

Affiliation:

1. University of Jeddah, Saudi Arabia

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3508072.3508085

Reference25 articles.

1. A Survey on Advanced Persistent Threats: Techniques, Solutions, Challenges, and Research Opportunities

2. A Semi-supervised Stacked Autoencoder Approach for Network Traffic Classification

3. Gbadebo Ayoade , Khandakar Akbar , Pracheta Sahoo , Yang Gao , Anoop Singhal , Kangkook Jee , Latifur Khan , and Anmol Agarwal . 2020 . Evolving Advanced Persistent Threat Detection Using Provenance Graph and Metric Learning. IEEE International Conference on Communications and Network Security (CNS 2020 ), Avignon, FR. https://doi.org/10.1109/CNS48642. 2020.9162264 10.1109/CNS48642.2020.9162264 Gbadebo Ayoade, Khandakar Akbar, Pracheta Sahoo, Yang Gao, Anoop Singhal, Kangkook Jee, Latifur Khan, and Anmol Agarwal. 2020. Evolving Advanced Persistent Threat Detection Using Provenance Graph and Metric Learning. IEEE International Conference on Communications and Network Security (CNS 2020), Avignon, FR. https://doi.org/10.1109/CNS48642.2020.9162264

4. Tero Bodström and Timo Hämäläinen . 2019. A Novel Deep Learning Stack for APT Detection. Applied Sciences 9, 6 ( 2019 ). https://doi.org/10.3390/app9061055 10.3390/app9061055 Tero Bodström and Timo Hämäläinen. 2019. A Novel Deep Learning Stack for APT Detection. Applied Sciences 9, 6 (2019). https://doi.org/10.3390/app9061055

5. A Method of Monitoring and Detecting APT Attacks Based on Unknown Domains

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