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Analyzing Autoencoder-Based Intrusion Detection System Performance · Peerford

Article · Journal · 2023

Analyzing Autoencoder-Based Intrusion Detection System Performance

Seiba Alhassan, Gaddafi Abdul-Salaam, Michael Asante, Yaw Marfo Missah, Ernest Domanaanmwi Ganaa

Journal of Information Security and Cybercrimes Research

Open access · Diamond

Read it 10.26735/ylxb6430

Citations: 0from other works
Field-weighted impact: 0.001.00 is the world average for its field and year
Among its field: 21st percentileby citations, against works of its field and year
Authors: 5from 2 institutions

Authors

5 authors across 2 institutions in 1 country

Seiba AlhassanFirst author
- Kwame Nkrumah University of Science and Technology (GH)
Gaddafi Abdul-Salaam
- Kwame Nkrumah University of Science and Technology (GH)
Michael Asante
- Kwame Nkrumah University of Science and Technology (GH)
Yaw Marfo Missah
- Kwame Nkrumah University of Science and Technology (GH)
as printed: Yaw Missah
Ernest Domanaanmwi GanaaSenior author
- Accra Technical University (GH)

Dr. Hilla Limann Technical University (GH)

as printed: Ernest Ganaa

Development goals

9Industry, innovation and infrastructure

Country

Ghana

Fields

A work can sit in several, each with a score

Network Security and Intrusion DetectionTopic
Advanced Malware Detection TechniquesTopic
Anomaly Detection Techniques and ApplicationsTopic