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This SpringerBrief addresses the security and privacy challenges in fog computing and proposes secure mechanisms to enhance fog-assisted IoT applications. It begins with an overview of the architecture and challenges in fog computing. The authors categorize existing privacy-enhancing techniques into identity-hidden techniques, location privacy protection, and data privacy enhancement, highlighting their importance in overcoming obstacles that hinder the development of IoT applications. They introduce three secure protocols tailored for smart parking navigation, mobile crowdsensing, and smart grid applications. In smart parking navigation, the authors propose a system that prevents identity leakage while ensuring efficient parking guidance via roadside units. For mobile crowdsensing, they present a privacy-preserving task allocation scheme that facilitates location-based task distribution without revealing participants' location or reputation. In the context of smart grids, an efficient smart metering protocol is introduced, allowing for real-time data collection with enhanced privacy through data aggregation. The brief concludes with insights on future research directions, emphasizing the balance between extending IoT device functionality and maintaining user security and privacy against dishonest fog nodes. It serves as a valuable resource for researchers and professionals focused on security and privacy in wireless commu
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Privacy-Enhancing Fog Computing and Its Applications, Xiaodong Lin
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- Année de publication
- 2018
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