Title
A comparative evaluation of unsupervised deep architectures for intrusion detection in sequential data streams
Abstract
•Thorough comparison of recurrent neural networks for anomaly detection.•Introduction of attentional component enabling explanations for end-users.•Evaluation focusing on ranking metrics with end-users in mind.
Year
DOI
Venue
2020
10.1016/j.eswa.2020.113577
Expert Systems with Applications
Keywords
DocType
Volume
Deep learning,Intrusion detection,Anomaly detection,Real-world data
Journal
159
ISSN
Citations 
PageRank 
0957-4174
1
0.35
References 
Authors
0
5
Name
Order
Citations
PageRank
Dusan Sovilj1423.94
Paul Budnarain210.35
Scott Sanner3196.35
Geoff Salmon410.35
Mohan Rao510.35