Smart City Gnosys
Smart city article details
| Title | Attack Classification Schema For Smart City Wsns |
|---|---|
| ID_Doc | 11012 |
| Authors | Garcia-Font, V; Garrigues, C; Rifà-Pous, H |
| Year | 2017 |
| Published | SENSORS, 17, 4 |
| DOI | http://dx.doi.org/10.3390/s17040771 |
| Abstract | Urban areas around the world are populating their streets with wireless sensor networks (WSNs) in order to feed incipient smart city IT systems with metropolitan data. In the future smart cities, WSN technology will have a massive presence in the streets, and the operation of municipal services will be based to a great extent on data gathered with this technology. However, from an information security point of view, WSNs can have failures and can be the target of many different types of attacks. Therefore, this raises concerns about the reliability of this technology in a smart city context. Traditionally, security measures in WSNs have been proposed to protect specific protocols in an environment with total control of a single network. This approach is not valid for smart cities, as multiple external providers deploy a plethora of WSNs with different security requirements. Hence, a new security perspective needs to be adopted to protect WSNs in smart cities. Considering security issues related to the deployment of WSNs as a main data source in smart cities, in this article, we propose an intrusion detection framework and an attack classification schema to assist smart city administrators to delimit the most plausible attacks and to point out the components and providers affected by incidents. We demonstrate the use of the classification schema providing a proof of concept based on a simulated selective forwarding attack affecting a parking and a sound WSN. |
| Author Keywords | anomaly detection; information security; intrusion detection; security information and event management; smart cities; wireless sensor networks |
Similar Articles
| Id | Similarity | Authors | Title | Published |
|---|---|---|---|---|
47696  | 0.883 | Mayur K.L.; Selvi M.; Santhosh Kumar S.V.N.; Thangaramya K.; Kannan A. | Secure Wireless Sensor Networks For Safe Cities | Digital Twin and Blockchain for Sensor Networks in Smart Cities (2025) |
| 19918 | 0.868 | Garcia-Font, V; Garrigues, C; Rifà-Pous, H | Difficulties And Challenges Of Anomaly Detection In Smart Cities: A Laboratory Analysis | SENSORS, 18, 10 (2018) |
| 37671 | 0.862 | Meleshko A.V.; Desnitsky V.A.; Kotenko I.V. | Modelling Attacks In Self-Organizing Wireless Sensor Networks Of Smart Cities | IOP Conference Series: Materials Science and Engineering, 971, 3 (2020) |
| 2061 | 0.862 | Wu, J; Ota, K; Dong, MX; Li, CX | A Hierarchical Security Framework For Defending Against Sophisticated Attacks On Wireless Sensor Networks In Smart Cities | IEEE ACCESS, 4 (2016) |
| 26374 | 0.857 | Devi M.; Nandal P.; Sehrawat H. | Federated Learning-Enabled Lightweight Intrusion Detection System For Wireless Sensor Networks: A Cybersecurity Approach Against Ddos Attacks In Smart City Environments | Intelligent Systems with Applications, 27 (2025) |
| 33339 | 0.853 | Pundir S.; Wazid M.; Singh D.P.; Das A.K.; Rodrigues J.J.P.C.; Park Y. | Intrusion Detection Protocols In Wireless Sensor Networks Integrated To Internet Of Things Deployment: Survey And Future Challenges | IEEE Access, 8 (2020) |
| 57304 | 0.851 | Obaidat M.A. | Threats And Vulnerabilities Of Wireless Sensor Networks In Smart Cities | The Rise of Smart Cities: Advanced Structural Sensing and Monitoring Systems (2022) |