Muhammad Hasnain1, Seung Ryul Jeong2, *, Muhammad Fermi Pasha3, Imran Ghani4
CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 729-752, 2020, DOI:10.32604/cmc.2020.010394
Abstract Performance anomaly detection is the process of identifying occurrences that
do not conform to expected behavior or correlate with other incidents or events in time
series data. Anomaly detection has been applied to areas such as fraud detection,
intrusion detection systems, and network systems. In this paper, we propose an anomaly
detection framework that uses dynamic features of quality of service that are collected in
a simulated setup. Three variants of recurrent neural networks-SimpleRNN, long short
term memory, and gated recurrent unit are evaluated. The results reveal that the proposed
method effectively detects anomalies in web services with high accuracy.… More >
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