| Title | SafeCity: Toward Safe and Secured Data Management Design for IoT-Enabled Smart City Planning |
|---|---|
| ID_Doc | 37633 |
| Authors | Zhang, H; Babar, M; Tariq, MU; Jan, MA; Menon, VG; Li, XW |
| Title | SafeCity: Toward Safe and Secured Data Management Design for IoT-Enabled Smart City Planning |
| Year | 2020 |
| Published | |
| Abstract | The interaction among different Internet of Things (IoT) sensors and devices become massive and insecure over the Internet as we probe to smart cities. These heterogeneous devices produce an enormous amount of data that is vulnerable to various malicious threats. The generated data need to be processed and analyzed in a secure fashion to make smart decisions. The smart urban planning is becoming a reality through the mass information generated by the Internet of Things (IoT). This paper exhibits a novel architecture, SafeCity, that limelight the ecosystem of smart cities consists of cameras, sensors, and other real-world physical devices. SafeCity is a three-layer architecture, i.e., a data security layer, a data computational layer, and a decision-making layer. At the first layer, payload-based symmetric encryption is used to secure the data from intruders by exchanging only the authentic data among the physical devices. The second layer is used for the computation of secured data. Finally, the third layer extracts visions from data. The secured exchange of data is ensured by using Raspberry Pi boards while the computation of data is tested on trustworthy datasets, using the Hadoop platform. The assessments disclose that SafeCity presents precious insights into a secured smart city in the context of sensors based IoT environment. |
| https://ieeexplore.ieee.org/ielx7/6287639/8948470/09160953.pdf |
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