The EU-funded WideHealth project aims to conduct research on pervasive eHealth and establish a sustainable network of research and dissemination across Europe.
Title: Federated Learning for Anomaly Detection in IoT Networks
Speaker: Ana Cholakoska
When: February 21, 2023 16:00 CET (15:00 in Portugal)
Where: zoom link shared before the session to those who register
Registration link: https://shre.ink/16thWideHealthSeminar
Abstract: The widespread use of IoT devices has contributed greatly to the continuous digitisation and modernisation of areas such as healthcare, facility management, transportation, and households. These devices allow for real-time mobile sensing, use input and then simplify and automate everyday tasks. However, like all other devices connected to a network, IoT devices are also subject to anomalous behaviour primarily due to security vulnerabilities or malfunction. Apart from this, they have limited resources and can hardly cope with such anomalies and attacks. Therefore, early detection of anomalies is of great importance for the proper functioning of the network and the protection of users’ personal data above all.
In the first part of the talk, an overview of the IoT architecture, protocols, and possible attacks will be given to better understand the need for introducing ML as a tool for intrusion detection purposes. Then, the federated learning approach for intrusion detection purposes in IoT networks will be discussed and compared with deep learning approaches. Finally, after presenting the results, conclusions will be summarized.
Short bio: Ana Cholakoska is a research and teaching assistant at the Faculty of Electrical Engineering and Information Technologies, Ss. Cyril and Methodius University in Skopje. Currently, she is part of the FEEIT team working on the WideHealth project, developing federated learning methods for anomaly detection in ambient assisted living environments, as well as improving privacy in IoT environments.