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Smart city article details
| Title | Edge-Assisted Puncturable Fine-Grained Task Distribution For The Iot-Oriented Crowdsensing |
|---|---|
| ID_Doc | 21818 |
| Authors | Jiang L.; Qin Z. |
| Year | 2022 |
| Published | Proceedings - IEEE Congress on Cybermatics: 2022 IEEE International Conferences on Internet of Things, iThings 2022, IEEE Green Computing and Communications, GreenCom 2022, IEEE Cyber, Physical and Social Computing, CPSCom 2022 and IEEE Smart Data, SmartData 2022 |
| DOI | http://dx.doi.org/10.1109/iThings-GreenCom-CPSCom-SmartData-Cybermatics55523.2022.00058 |
| Abstract | Internet of Things (IoT)-based mobile crowdsensing system has been increasingly widely deployed in data-driven smart city construction for its high efficiency, participation and flexibility. However, the mobile crowdsensing system may suffer unauthorized access to the task during the task distribution, thus imposing a threat to the city security and personal privacy. To deal with this threat, in this paper we propose an edge-assisted puncturable attribute-based access control scheme. This scheme provides efficient, one-to-many secure data sharing and delegates most of the computational overhead of resource-constrained terminal devices to the edge device. Then we design and integrate the Bloom filter into the proposed scheme to cope with the key exposure without key update. We provide rigorous security proof and the analysis of security properties. Theoretical comparison and experimental results demonstrate the feasibility and practicality of our scheme. © 2022 IEEE. |
| Author Keywords | Attribute-based access control; Edge computing; Internet of Things; Mobile crowdsensing |
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