Paper Info
Title
PESKEA: Anomaly Detection Framework for Profiling Kernel Event Attributes in Embedded Systems
Abstract
In the software development life cycle, we use the execution traces of a given application to examine the behavior of the software when an error occurs or to monitor the software performance and compliance. However, this type of application trace analysis focuses on checking the performance of the software against its design goals. Conversely, the operating system (OS) sits between the application...
Year
DOI
Venue
2021
10.1109/TETC.2020.2971251
IEEE Transactions on Emerging Topics in Computing
Keywords
DocType
Volume
Anomaly detection,Embedded systems,Feature extraction,Monitoring,Kernel,Hardware
Journal
9
Issue
ISSN
Citations 
2
2168-6750
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Okwudili M. Ezeme100.68
Akramul Azim23911.82
Qusay H. Mahmoud3844112.10