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Sensors 2017, 17(8), 1744; https://doi.org/10.3390/s17081744

Crowd Sensing-Enabling Security Service Recommendation for Social Fog Computing Systems

1
School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
2
School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China
3
School of Marxism, Zhejiang University of Science and Technology, Hangzhou 310023, China
*
Author to whom correspondence should be addressed.
Received: 29 April 2017 / Revised: 9 July 2017 / Accepted: 24 July 2017 / Published: 30 July 2017
(This article belongs to the Special Issue Security and Privacy Challenges in Emerging Fog Computing)
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Abstract

Fog computing, shifting intelligence and resources from the remote cloud to edge networks, has the potential of providing low-latency for the communication from sensing data sources to users. For the objects from the Internet of Things (IoT) to the cloud, it is a new trend that the objects establish social-like relationships with each other, which efficiently brings the benefits of developed sociality to a complex environment. As fog service become more sophisticated, it will become more convenient for fog users to share their own services, resources, and data via social networks. Meanwhile, the efficient social organization can enable more flexible, secure, and collaborative networking. Aforementioned advantages make the social network a potential architecture for fog computing systems. In this paper, we design an architecture for social fog computing, in which the services of fog are provisioned based on “friend” relationships. To the best of our knowledge, this is the first attempt at an organized fog computing system-based social model. Meanwhile, social networking enhances the complexity and security risks of fog computing services, creating difficulties of security service recommendations in social fog computing. To address this, we propose a novel crowd sensing-enabling security service provisioning method to recommend security services accurately in social fog computing systems. Simulation results show the feasibilities and efficiency of the crowd sensing-enabling security service recommendation method for social fog computing systems. View Full-Text
Keywords: fog computing; social networks; service discovery; service recommendation fog computing; social networks; service discovery; service recommendation
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Wu, J.; Su, Z.; Wang, S.; Li, J. Crowd Sensing-Enabling Security Service Recommendation for Social Fog Computing Systems. Sensors 2017, 17, 1744.

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