Author: Víctor García Font
Programme: Doctoral Programme in Network and Information Technologies
Language: English
Supervisors: Dr. Carles Garrigues Olivella and Dr. Helena Rifà Pous
Faculty / Institute: Doctoral School UOC
Subjects: Computer Science
Key words: Information security, smart city, wireless sensor networks, intrusion detection systems, anomaly detection, cybersecurity
Area of knowledge: Network and Information Technologies
Summary
This thesis proposes an intrusion detection platform which reveals attacks in smart city wireless sensor networks (WSN). The platform is designed taking into account the needs of smart city administrators, who need access to a centralized architecture that can manage security alarms in a highly heterogeneous and distributed system. In this thesis, we identify the various necessary steps from gathering WSN data to running the detection techniques and we evaluate whether the procedure is scalable and capable of handling typical smart city data. Moreover, we compare several anomaly detection algorithms and we observe that one-class support vector machines constitute the most suitable multivariate technique to reveal attacks, taking into account the requirements in this context. Finally, we propose a classification schema to assist administrators in identifying the types of attacks compromising their networks.