Federated Cyberattack Detection for Internet of Things-Enabled Smart Cities
- Resource Type
- Periodical
- Authors
- Matheu, S.N.; Marmol, E.; Hernandez-Ramos, J.L.; Skarmeta, A.; Baldini, G.
- Source
- Computer. 55(12):65-73 Dec, 2022
- Subject
- Computing and Processing
Data privacy
Smart cities
Federated learning
Telecommunication traffic
Internet
Faces
Cyberattack
- Language
- ISSN
- 0018-9162
1558-0814
While attack detection is key to realize trustworthy smart cities, the use of large amounts of network traffic data by machine learning techniques can lead to privacy issues for citizens. To face this issue, we propose a federated learning approach in the context of Internet of Things-enabled smart cities integrating the Threat and Manufacturer Usage Description files as a prevention/mitigation approach.