Abstract
Smart city is gaining a significant attention all around the world. Narrowband technologies would have strong impact on achieving the smart city promises to its citizens with its powerful and efficient spectrum. The expected diversity of applications, different data structures and high volume of connecting devices for smart cities increase the persistent need to apply narrowband technologies. However, narrowband technologies have recognized limitations regarding security which make them an attractive target to cyber-attacks. In this paper, a novel platform architecture to secure smart city against cyber attackers is presented. The framework is providing a threat deep learning-based model to detect attackers based on users data behavior. The proposed architecture could be considered as an attempt toward developing a universal model to identify and block Denial of Service (DoS) attackers in a real time for smart city applications.
| Original language | English |
|---|---|
| Title of host publication | 2017 27th International Telecommunication Networks and Applications Conference, ITNAC 2017 |
| Publisher | IEEE, Institute of Electrical and Electronics Engineers |
| Pages | 1-6 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781509067961 |
| ISBN (Print) | 9781509067978 |
| DOIs | |
| Publication status | Published - 22 Nov 2017 |
| Event | 27th International Telecommunication Networks and Applications Conference - Melbourne, Australia Duration: 22 Nov 2017 → 24 Nov 2017 |
Publication series
| Name | 2017 27th International Telecommunication Networks and Applications Conference, ITNAC 2017 |
|---|---|
| Volume | 2017-January |
Conference
| Conference | 27th International Telecommunication Networks and Applications Conference |
|---|---|
| Abbreviated title | ITNAC 2017 |
| Country/Territory | Australia |
| City | Melbourne |
| Period | 22/11/17 → 24/11/17 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 11 Sustainable Cities and Communities
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