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Machine Learning Applications for Anomaly Detection

Machine Learning Applications for Anomaly Detection
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Author(s): Teguh Wahyono (Satya Wacana Christian University, Indonesia) and Yaya Heryadi (Bina Nusantara University, Indonesia)
Copyright: 2019
Pages: 35
Source title: Computational Intelligence in the Internet of Things
Source Author(s)/Editor(s): Hindriyanto Dwi Purnomo (Satya Wacana Christian University, Indonesia)
DOI: 10.4018/978-1-5225-7955-7.ch003

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Abstract

The aim of this chapter is to describe and analyze the application of machine learning for anomaly detection. The study regarding the anomaly detection is a very important thing. The various phenomena often occur related to the anomaly study, such as the occurrence of an extreme climate change, the intrusion detection for the network security, the fraud detection for e-banking, the diagnosis for engines fault, the spacecraft anomaly detection, the vessel track, and the airline safety. This chapter is an attempt to provide a structured and a broad overview of extensive research on anomaly detection techniques spanning multiple research areas and application domains. Quantitative analysis meta-approach is used to see the development of the research concerned with those matters. The learning is done on the method side, the techniques utilized, the application development, the technology utilized, and the research trend, which is developed.

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