Machine Learning Techniques

Roaa Al Feel, an early-career researcher, discusses her passion for using data science for social good. She uses data to reflect living conditions of society, and in the paper published with Patterns in November, the team explores machine learning techniques for the detection of fake news around the Syrian war, demonstrating the efficacy of meta-learning techniques when tackling datasets of a modest size.
This study provides new insights into the potential use of machine learning in hydrological simulations.
Elsevier, International Journal of Critical Infrastructure Protection, Volume 31, December 2020
Early and accurate anomaly detection in critical infrastructure (CI), such as water treatment plants and electric power grid, is necessary to avoid plant damage and service disruption. Several machine learning techniques have been employed for the design of an effective anomaly detector in such systems. However, threats such as from insiders and state actors, introduce challenges in the design of an effective anomaly detector. This work presents a multi-layer perceptron (MLP) based anomaly detector that uses an unsupervised approach to safeguard CI from the adverse impacts of cyber-attacks.