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Generative Adversarial Networks for Anomaly Detection on Telco multivariate time series
Sara Malacarne (Telenor) & Massimiliano Ruocco (SINTEF & NTNU) will give a talk on "Generative Adversarial Networks for Anomaly Detection on Telco multivariate time series".

Abstract: Anomaly detection is the process of identifying interesting events that deviate from the data’s “normal” behaviour and has many important applications to real case scenarios. In the telecommunications domain, efficient and accurate anomaly detection is vital to be able to continuously monitor the network infrastructure key performance indicators (KPIs) and alert for possible incidents in time.

Network KPIs are in the form of multivariate time series which, for costs reasons, are not labelled. The main challenges for performing anomaly detection on network data are the following: 1) it is an unsupervised learning problem, 2) temporal and feature-wise correlations have to be exploited in order to reduce false positives, 3) anomalies are not necessarily rare events in the data, 4) the data is high-dimensional.

This work is a first attempt to simultaneously address the first three challenges listed above, with the use of a novel Generative Adversarial Network (GAN), called RegGAN. GANs present in the literature -- such as MAD-GAN, BeatGAN, TadGAN -- have serious drawbacks on highly contaminated data, that is, data with frequent abnormal events. Thus, RegGAN was specifically built to overcome this issue, and it has proven to be robust to contamination experiments performed on open benchmark datasets.

About the speakers:

Sara Malacarne is a Research Scientist in the Analytics and AI team at Telenor Research. Sara has PhD in pure math. Since joining Telenor Research in 2018, she has been developing an interests towards AI/DL methods for solving tasks in the time series domain for 4G/5G Telco data.

Massimiliano Ruocco is a Senior Researcher at SINTEF Digital and Adj. Associate Professor at the Dept of Computer Science (IDI), at NTNU.

Nov 12, 2021 01:00 PM in Oslo

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